# Tesserae

> Auto-generated wiki layer for AI agents and humans. Browse the same content as HTML at /, or fetch graph.jsonld for the structured view.

## Sources

- [Activity Summary + Citation-Name Fix — Design](sources/activity-summary-citation-name-fix-design.html): - **uses_metric** → mAP _(Metric)_
- [Activity Summary + Citation-Name Fix — Implementation Plan](sources/activity-summary-citation-name-fix-implementation-plan.html): - **uses_metric** → mAP _(Metric)_
- [AgentRunbook-style multi-granularity memory for Tesserae](sources/agentrunbook-style-multi-granularity-memory-for-tesserae.html): - **uses_metric** → Recall _(Metric)_
- [Architecture](sources/architecture.html): - **uses_metric** → mAP _(Metric)_
- [Architecture (fixture](sources/architecture-fixture.html)
- [Automatic consolidation — the engine's sleep cycle](sources/automatic-consolidation-the-engine-s-sleep-cycle.html)
- [Backend end-of-life: understand-anything (now) and cognee (0.19](sources/backend-end-of-life-understand-anything-now-and-cognee-0-19.html)
- [Build the static site at `.tesserae/site/` from the compiled graph. Includes the 3D graph view, per-node wiki pages, search index, and the bundled ask widget. Pair with `/tesserae:serve` to view locally.](sources/build-the-static-site-at-tesserae-site-from-the-compiled-graph-includes-the-3d-g-5f3d8572.html)
- [Chrome Web Store listing — Clip to Tesserae](sources/chrome-web-store-listing-clip-to-tesserae.html)
- [Claim-Level Citation-Support Lint Implementation Plan](sources/claim-level-citation-support-lint-implementation-plan.html): - **uses_metric** → mAP _(Metric)_
- [Claude Code plugin](sources/claude-code-plugin.html): - **uses_metric** → Recall _(Metric)_
- [Claude Code plugin for Tesserae — design](sources/claude-code-plugin-for-tesserae-design.html)
- [Claude Code plugin for Tesserae — implementation plan](sources/claude-code-plugin-for-tesserae-implementation-plan.html)
- [CLI Redesign — crystal-clear command tree (clean break](sources/cli-redesign-crystal-clear-command-tree-clean-break.html)
- [CLI Redesign Implementation Plan (v0.6.0](sources/cli-redesign-implementation-plan-v0-6-0.html): - **uses_metric** → F1 _(Metric)_
- [Clip to Tesserae](sources/clip-to-tesserae.html)
- [Community-Page Sources Footer (Scoped-Down Source-Map Provenance) Implementation Plan](sources/community-page-sources-footer-scoped-down-source-map-provenance-implementation-plan.html): - **uses_metric** → mAP _(Metric)_
- [Compile Output Snapshot Hash Implementation Plan](sources/compile-output-snapshot-hash-implementation-plan.html)
- [Cross-project federated graph mode — design sketch](sources/cross-project-federated-graph-mode-design-sketch.html): - **uses_metric** → Precision _(Metric)_ - **uses_metric** → Recall _(Metric)_
- [Daily Research Digest — 2026-04-25](sources/daily-research-digest-2026-04-25.html): - **mentioned_in** → Image Generators are Generalist Vision Learners _(Paper)_
- [Daily Research Digest — 2026-04-26](sources/daily-research-digest-2026-04-26.html)
- [Daily session chunks — `.tesserae/session_chunks.db`](sources/daily-session-chunks-tesserae-session-chunks-db.html)
- [Decisions Query Implementation Plan](sources/decisions-query-implementation-plan.html)
- [Delta-Scoped Code-Graph Regeneration: the No-Op Extraction Cache (OpenWiki Candidate F](sources/delta-scoped-code-graph-regeneration-the-no-op-extraction-cache-openwiki-candidate-f.html)
- [Demo corpus licenses](sources/demo-corpus-licenses.html): - **evaluated_on** → Mip-NeRF 360 _(Benchmark)_
- [Distillery — layered per-agent knowledge graphs](sources/distillery-layered-per-agent-knowledge-graphs.html): - **evaluated_on** → MATH _(Benchmark)_ - **uses_metric** → Recall _(Metric)_ - **uses_metric** → mAP _(Metric)_
- [div align="center">](sources/div-align-center.html)
- [Example: `/tesserae:ask \"what did we decide about extractor dedup?\"`](sources/example-tesserae-ask-what-did-we-decide-about-extractor-dedup.html)
- [Examples:](sources/examples.html)
- [Extraction-Feedback Loop Implementation Plan](sources/extraction-feedback-loop-implementation-plan.html)
- [Extraction-Feedback Loop — v1 Design](sources/extraction-feedback-loop-v1-design.html)
- [Feature Map](sources/feature-map.html): - **uses_metric** → mAP _(Metric)_
- [Federation MVP — file-by-file build spec](sources/federation-mvp-file-by-file-build-spec.html): - **uses_metric** → Recall _(Metric)_ - **uses_metric** → mAP _(Metric)_
- [Frontend redesign — annotated route walkthrough](sources/frontend-redesign-annotated-route-walkthrough.html): - **uses_metric** → mAP _(Metric)_
- [Git-Delta Staleness Signal for the Code Graph (OpenWiki Candidate D](sources/git-delta-staleness-signal-for-the-code-graph-openwiki-candidate-d.html): - **uses_metric** → mAP _(Metric)_
- [Global Engine (Fleet Daemon) — Design](sources/global-engine-fleet-daemon-design.html)
- [Global Engine (Fleet Daemon) Implementation Plan](sources/global-engine-fleet-daemon-implementation-plan.html)
- [Graph View v1 Implementation Plan](sources/graph-view-v1-implementation-plan.html): - **uses_metric** → mAP _(Metric)_
- [Graph View v1 — "sophisticated + production-ready" Design](sources/graph-view-v1-sophisticated-production-ready-design.html): - **uses_metric** → mAP _(Metric)_
- [Harness session history](sources/harness-session-history.html)
- [HN / Twitter launch post draft](sources/hn-twitter-launch-post-draft.html): - **uses_metric** → Recall _(Metric)_
- [Idempotent Agent-Instruction Pointer Install Plan](sources/idempotent-agent-instruction-pointer-install-plan.html)
- [Installation](sources/installation.html)
- [jokerized/tesserae](sources/jokerized-tesserae.html)
- [Layered agent memory — per-agent knowledge graphs](sources/layered-agent-memory-per-agent-knowledge-graphs.html)
- [Live Serve Sessions Implementation Plan](sources/live-serve-sessions-implementation-plan.html): - **uses_metric** → mAP _(Metric)_
- [LLM-Backed Synthesis Prose](sources/llm-backed-synthesis-prose.html)
- [MCP — wire Tesserae into Claude Code, Codex, Cursor](sources/mcp-wire-tesserae-into-claude-code-codex-cursor.html)
- [Memex / OKF research — decision document](sources/memex-okf-research-decision-document.html)
- [Obsidian bidirectional sync — proposed design](sources/obsidian-bidirectional-sync-proposed-design.html)
- [Obsidian — open the compiled wiki as a real vault](sources/obsidian-open-the-compiled-wiki-as-a-real-vault.html)
- [Print a one-screen overview of this Tesserae project: graph node/edge counts, last compile timestamp, number of imported sessions, and the configured Obsidian vault path. Pure read — never mutates anything.](sources/print-a-one-screen-overview-of-this-tesserae-project-graph-node-edge-counts-last-5842b016.html)
- [Privacy Policy — Clip to Tesserae](sources/privacy-policy-clip-to-tesserae.html)
- [Publishing Checklist](sources/publishing-checklist.html): - **uses_metric** → mAP _(Metric)_
- [Publishing "Clip to Tesserae" to the Chrome Web Store](sources/publishing-clip-to-tesserae-to-the-chrome-web-store.html)
- [Quickstart](sources/quickstart.html): - **uses_metric** → mAP _(Metric)_
- [Quickstart (fixture](sources/quickstart-fixture.html)
- [RAG-Anything multimodal companion](sources/rag-anything-multimodal-companion.html)
- [Remove the active-project concept — design](sources/remove-the-active-project-concept-design.html)
- [Research Graph Extraction Prompt](sources/research-graph-extraction-prompt.html): - **uses_metric** → mAP _(Metric)_
- [Run `tesserae_setup_plan` for the current working directory. Show the](sources/run-tesserae-setup-plan-for-the-current-working-directory-show-the.html)
- [Run this once per project; subsequent compiles read from the cached `harness_sessions/` directory rather than re-scanning the filesystem.](sources/run-this-once-per-project-subsequent-compiles-read-from-the-cached-harness-sessi-7d1ad645.html)
- [Scheduled CI refresh with the output-snapshot gate](sources/scheduled-ci-refresh-with-the-output-snapshot-gate.html)
- [Self-dogfood Demo](sources/self-dogfood-demo.html)
- [Session graph](sources/session-graph.html)
- [Session graph extractor — design](sources/session-graph-extractor-design.html): - **uses_metric** → SSIM _(Metric)_ - **uses_metric** → mAP _(Metric)_
- [Session graph extractor — implementation plan](sources/session-graph-extractor-implementation-plan.html)
- [Setup Rewrite Implementation Plan](sources/setup-rewrite-implementation-plan.html)
- [Setup rewrite — sophisticated wizard, MCP plan/apply, environment detection](sources/setup-rewrite-sophisticated-wizard-mcp-plan-apply-environment-detection.html)
- [Start the dev HTTP server against `.tesserae/site/`. Default port 8765. Pass `--host 0.0.0.0` to expose on the LAN.](sources/start-the-dev-http-server-against-tesserae-site-default-port-8765-pass-host-0-0-16959ad3.html)
- [Synthesis fixtures](sources/synthesis-fixtures.html)
- [Tech Stack:** Python 3 stdlib only, pytest via `.venv/bin/python`. No new deps.](sources/tech-stack-python-3-stdlib-only-pytest-via-venv-bin-python-no-new-deps.html)
- [Tesserae](sources/tesserae.html): - **uses_metric** → Recall _(Metric)_
- [Tesserae as a Context Engine — Gap Analysis](sources/tesserae-as-a-context-engine-gap-analysis.html): - **reports_result** → top-1=2 _(Result)_
- [Tesserae Chrome Extension — Design](sources/tesserae-chrome-extension-design.html)
- [Tesserae — Claude Code plugin](sources/tesserae-claude-code-plugin.html): - **uses_metric** → Recall _(Metric)_
- [tesserae compile $ARGUMENTS`](sources/tesserae-compile-arguments.html)
- [Tesserae → Context Engine — Phased Roadmap](sources/tesserae-context-engine-phased-roadmap.html): - **reports_result** → top-1=2 _(Result)_
- [Tesserae Demo Corpus: 3D Reconstruction (2016–2024](sources/tesserae-demo-corpus-3d-reconstruction-2016-2024.html): - **uses_metric** → mAP _(Metric)_
- [Tesserae Demo Corpus — Inventory](sources/tesserae-demo-corpus-inventory.html): - **evaluated_on** → Mip-NeRF 360 _(Benchmark)_
- [tesserae doctor` — project health checks](sources/tesserae-doctor-project-health-checks.html)
- [tesserae ingest`](sources/tesserae-ingest.html)
- [tesserae ingest` Command Implementation Plan](sources/tesserae-ingest-command-implementation-plan.html)
- [tesserae ingest` — single source → KB, incremental + reconciled](sources/tesserae-ingest-single-source-kb-incremental-reconciled.html)
- [tesserae:pointer:begin -->](sources/tesserae-pointer-begin.html)
- [Tesserae v0.10.0 — interop, fast transcript search, and machine-wide setup](sources/tesserae-v0-10-0-interop-fast-transcript-search-and-machine-wide-setup.html)
- [Tesserae v0.10.1 — config visibility + cognee polish](sources/tesserae-v0-10-1-config-visibility-cognee-polish.html)
- [Tesserae v0.11.0 — cross-project federated graph](sources/tesserae-v0-11-0-cross-project-federated-graph.html): - **uses_metric** → Precision _(Metric)_ - **uses_metric** → Recall _(Metric)_
- [Tesserae v0.12.0 — multi-project by default](sources/tesserae-v0-12-0-multi-project-by-default.html): - **uses_metric** → mAP _(Metric)_
- [Tesserae v0.12.1 — every endpoint routes in fleet serve](sources/tesserae-v0-12-1-every-endpoint-routes-in-fleet-serve.html)
- [Tesserae v0.12.2 — daemon fd-exhaustion + recency-aware ask](sources/tesserae-v0-12-2-daemon-fd-exhaustion-recency-aware-ask.html): - **uses_metric** → Recall _(Metric)_
- [Tesserae v0.13.0 — the LLM concept layer is the default](sources/tesserae-v0-13-0-the-llm-concept-layer-is-the-default.html)
- [Tesserae v0.13.1 — manage compile sources (local & global](sources/tesserae-v0-13-1-manage-compile-sources-local-global.html)
- [Tesserae v0.13.2 — clip endpoint trusts only the published extension](sources/tesserae-v0-13-2-clip-endpoint-trusts-only-the-published-extension.html)
- [Tesserae v0.14.0 — daily & weekly activity summaries](sources/tesserae-v0-14-0-daily-weekly-activity-summaries.html)
- [Tesserae v0.15.0 — query decisions across projects and time](sources/tesserae-v0-15-0-query-decisions-across-projects-and-time.html)
- [Tesserae v0.16.0 — the serve page goes live](sources/tesserae-v0-16-0-the-serve-page-goes-live.html)
- [Tesserae v0.17.0 — the compile path learns from its peers](sources/tesserae-v0-17-0-the-compile-path-learns-from-its-peers.html)
- [Tesserae v0.18.0 — ask answers, the engine remembers, doctor heals](sources/tesserae-v0-18-0-ask-answers-the-engine-remembers-doctor-heals.html): - **uses_metric** → Recall _(Metric)_
- [Tesserae v0.19.0 — one graph, no passengers](sources/tesserae-v0-19-0-one-graph-no-passengers.html)
- [Tesserae v0.19.1 — doctor stops second-guessing live daemons](sources/tesserae-v0-19-1-doctor-stops-second-guessing-live-daemons.html)
- [Tesserae v0.2.0 — Typed retrieval, code graph, ontology evolution](sources/tesserae-v0-2-0-typed-retrieval-code-graph-ontology-evolution.html): - **reports_result** → top-1=0 _(Result)_ - **uses_metric** → Recall _(Metric)_ - **uses_metric** → mAP _(Metric)_
- [Tesserae v0.20.0 — the MCP surface catches up](sources/tesserae-v0-20-0-the-mcp-surface-catches-up.html)
- [Tesserae v0.20.1 — long sessions, fully captured](sources/tesserae-v0-20-1-long-sessions-fully-captured.html)
- [Tesserae v0.20.2 — the model reads everything now](sources/tesserae-v0-20-2-the-model-reads-everything-now.html): - **uses_metric** → mAP _(Metric)_
- [Tesserae v0.21.0 — layered agent memory](sources/tesserae-v0-21-0-layered-agent-memory.html): - **uses_metric** → Recall _(Metric)_
- [Tesserae v0.22.0 — the agent-memory CLI, finished](sources/tesserae-v0-22-0-the-agent-memory-cli-finished.html)
- [Tesserae v0.22.1 — `agents init` explains a flat org](sources/tesserae-v0-22-1-agents-init-explains-a-flat-org.html)
- [Tesserae v0.23.0 — the engine's sleep cycle](sources/tesserae-v0-23-0-the-engine-s-sleep-cycle.html)
- [Tesserae v0.24.0 — the full sleep cycle: forget by disuse, discover connections](sources/tesserae-v0-24-0-the-full-sleep-cycle-forget-by-disuse-discover-connections.html)
- [Tesserae v0.25.0 — Descent: navigate any graph inside one context window](sources/tesserae-v0-25-0-descent-navigate-any-graph-inside-one-context-window.html): - **uses_metric** → mAP _(Metric)_
- [Tesserae v0.25.1 — the compile no longer wedges, and degraded docs are recoverable](sources/tesserae-v0-25-1-the-compile-no-longer-wedges-and-degraded-docs-are-recoverable.html)
- [Tesserae v0.26.0 — compiles that finish, and say what they did](sources/tesserae-v0-26-0-compiles-that-finish-and-say-what-they-did.html)
- [Tesserae v0.27.0 — agents can write to the graph, and ask it what it licenses](sources/tesserae-v0-27-0-agents-can-write-to-the-graph-and-ask-it-what-it-licenses.html): - **reports_result** → recall=7 _(Result)_ - **uses_metric** → Precision _(Metric)_ - **uses_metric** → Recall _(Metric)_
- [Tesserae v0.28.0 — hooks that cannot spend your money by accident](sources/tesserae-v0-28-0-hooks-that-cannot-spend-your-money-by-accident.html)
- [Tesserae v0.28.2 — `verify_claim` from the shell, and a doc that was lying about it](sources/tesserae-v0-28-2-verify-claim-from-the-shell-and-a-doc-that-was-lying-about-it.html): - **uses_metric** → mAP _(Metric)_
- [Tesserae v0.28.3 — the extractor's one-turn cap, and what it silently cost](sources/tesserae-v0-28-3-the-extractor-s-one-turn-cap-and-what-it-silently-cost.html)
- [Tesserae v0.28.4 — your other accounts were never being used](sources/tesserae-v0-28-4-your-other-accounts-were-never-being-used.html)
- [Tesserae v0.3.0 — Prose-to-code links, polyglot code graph, live sync](sources/tesserae-v0-3-0-prose-to-code-links-polyglot-code-graph-live-sync.html): - **uses_metric** → Precision _(Metric)_ - **uses_metric** → mAP _(Metric)_
- [Tesserae v0.4.0 — Extraction-feedback loop, research mode, evolution on by default](sources/tesserae-v0-4-0-extraction-feedback-loop-research-mode-evolution-on-by-default.html): - **uses_metric** → mAP _(Metric)_
- [Tesserae v0.5.0 — The engine spine and the On-Demand Context Compiler](sources/tesserae-v0-5-0-the-engine-spine-and-the-on-demand-context-compiler.html): - **reports_result** → top-1=2 _(Result)_ - **uses_metric** → mAP _(Metric)_
- [Tesserae v0.6.0 — A crystal-clear CLI](sources/tesserae-v0-6-0-a-crystal-clear-cli.html)
- [Tesserae v0.6.1 — CLI quality-of-life + a codex provider fix](sources/tesserae-v0-6-1-cli-quality-of-life-a-codex-provider-fix.html)
- [Tesserae v0.7.0 — `tesserae ask` answers without an API key](sources/tesserae-v0-7-0-tesserae-ask-answers-without-an-api-key.html)
- [Tesserae v0.7.1 — `tesserae ingest` merges one source without a full recompile](sources/tesserae-v0-7-1-tesserae-ingest-merges-one-source-without-a-full-recompile.html)
- [Tesserae v0.7.2 — discovery and compile no longer hang](sources/tesserae-v0-7-2-discovery-and-compile-no-longer-hang.html)
- [Tesserae v0.8.0 — `tesserae engine --all`: one engine for every project](sources/tesserae-v0-8-0-tesserae-engine-all-one-engine-for-every-project.html)
- [Tesserae v0.8.1 — fleet field fixes: no fd storms, fast restarts, quiet logs](sources/tesserae-v0-8-1-fleet-field-fixes-no-fd-storms-fast-restarts-quiet-logs.html)
- [Tesserae v0.8.2 — web clipper: one-click ingestion from the browser](sources/tesserae-v0-8-2-web-clipper-one-click-ingestion-from-the-browser.html)
- [Tesserae v0.9.0 — AgentRunbook memory + an LLM backend you can actually see](sources/tesserae-v0-9-0-agentrunbook-memory-an-llm-backend-you-can-actually-see.html)
- [Tesserae v0.9.1 — engine & session-capture bugfixes](sources/tesserae-v0-9-1-engine-session-capture-bugfixes.html)
- [tesserae vault sync $ARGUMENTS`](sources/tesserae-vault-sync-arguments.html)
- [The final line of output is a deterministic summary parsed from the compile log: `nodes=NNN edges=NNN processed=NNN sessions=NNN vault_orphans_pruned=NNN`.](sources/the-final-line-of-output-is-a-deterministic-summary-parsed-from-the-compile-log-eaf4a581.html)
- [Tuning reference — environment variables](sources/tuning-reference-environment-variables.html): - **uses_metric** → mAP _(Metric)_
- [Using Tesserae from inside Claude Code](sources/using-tesserae-from-inside-claude-code.html)
- [Web Clipper (Chrome extension](sources/web-clipper-chrome-extension.html)
- [Weekly Research Digest — 2026-W17](sources/weekly-research-digest-2026-w17.html): - **mentioned_in** → Image Generators are Generalist Vision Learners _(Paper)_

## Papers

- [2D Gaussian Splatting for Geometrically Accurate Radiance Fields](papers/2d-gaussian-splatting-for-geometrically-accurate-radiance-fields.html): - **addresses** → Novel View Synthesis _(Task)_ - **belongs_to_approach_family** → Gaussian Splatting Reconstruction _(ApproachFamily)_ - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses** → Depth Map _(TechnicalTer…
- [3D Gaussian Splatting for Real-Time Radiance Field Rendering](papers/3d-gaussian-splatting-for-real-time-radiance-field-rendering.html): - **addresses** → Visual SLAM _(ResearchTopic)_ - **belongs_to_approach_family** → Gaussian Splatting Reconstruction _(ApproachFamily)_ - **implemented_in** → About graphdeco-inria/gaussian-splatting _(Repository)_ - **part_of** → 3D/4D Vi…
- [4D Gaussian Splatting for Real-Time Dynamic Scene Rendering](papers/4d-gaussian-splatting-for-real-time-dynamic-scene-rendering.html): - **belongs_to_approach_family** → Dynamic Gaussian Splatting _(ApproachFamily)_ - **belongs_to_approach_family** → Gaussian Splatting Reconstruction _(ApproachFamily)_ - **implemented_in** → About hustvl/4DGaussians _(Repository)_ - **par…
- [4D-Rotor Gaussian Splatting: Towards Efficient Novel View Synthesis for Dynamic Scenes](papers/4d-rotor-gaussian-splatting-towards-efficient-novel-view-synthesis-for-dynamic-scenes.html): - **addresses** → Novel View Synthesis _(Task)_ - **belongs_to_approach_family** → Dynamic Gaussian Splatting _(ApproachFamily)_ - **belongs_to_approach_family** → Gaussian Splatting Reconstruction _(ApproachFamily)_ - **part_of** → 3D/4D…
- [AGG: Amortized Generative 3D Gaussians for Single Image to 3D](papers/agg-amortized-generative-3d-gaussians-for-single-image-to-3d.html): - **belongs_to_approach_family** → Gaussian Splatting Reconstruction _(ApproachFamily)_ - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses** → Gaussian Splatting _(MethodologicalConcept)_ - **uses_metric** → LPIPS _…
- [BARF: Bundle-Adjusting Neural Radiance Fields](papers/barf-bundle-adjusting-neural-radiance-fields.html): - **addresses** → Visual SLAM _(ResearchTopic)_ - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses_dataset** → Blender _(Dataset)_ - **uses_metric** → LPIPS _(Metric)_ - **uses_metric** → PSNR _(Metric)_ - **uses_me…
- [Co-SLAM: Joint Coordinate and Sparse Parametric Encodings for Neural Real-Time SLAM](papers/co-slam-joint-coordinate-and-sparse-parametric-encodings-for-neural-real-time-slam.html): - **addresses** → Visual SLAM _(ResearchTopic)_ - **belongs_to_approach_family** → Gaussian Splatting Reconstruction _(ApproachFamily)_ - **evaluated_on** → Replica _(Benchmark)_ - **evaluated_on** → ScanNet _(Benchmark)_ - **introduces**…
- [DeepV2D: Video to Depth with Differentiable Structure from Motion](papers/deepv2d-video-to-depth-with-differentiable-structure-from-motion.html): - **addresses** → Visual SLAM _(ResearchTopic)_ - **introduces** → DeepV2D _(Algorithm)_ - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses_metric** → LPIPS _(Metric)_ - **uses_metric** → PSNR _(Metric)_ - **uses_me…
- [Direct Sparse Odometry](papers/direct-sparse-odometry.html): - **addresses** → Visual SLAM _(ResearchTopic)_ - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses_metric** → Accuracy _(Metric)_ - **uses_metric** → LPIPS _(Metric)_ - **uses_metric** → PSNR _(Metric)_ - **uses_met…
- [DreamFusion: Text-to-3D using 2D Diffusion](papers/dreamfusion-text-to-3d-using-2d-diffusion.html): - **implemented_in** → About ashawkey/stable-dreamfusion _(Repository)_ - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses_metric** → LPIPS _(Metric)_ - **uses_metric** → PSNR _(Metric)_ - **uses_metric** → SSIM _(M…
- [DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation](papers/dreamgaussian-generative-gaussian-splatting-for-efficient-3d-content-creation.html): - **belongs_to_approach_family** → Gaussian Splatting Reconstruction _(ApproachFamily)_ - **implemented_in** → About dreamgaussian/dreamgaussian _(Repository)_ - **introduces** → DreamGaussian _(Algorithm)_ - **part_of** → 3D/4D Vision and…
- [DROID-SLAM: Deep Visual SLAM for Monocular, Stereo, and RGB-D Cameras](papers/droid-slam-deep-visual-slam-for-monocular-stereo-and-rgb-d-cameras.html): - **addresses** → Visual SLAM _(ResearchTopic)_ - **implemented_in** → About princeton-vl/DROID-SLAM _(Repository)_ - **introduces** → DROID-SLAM _(Algorithm)_ - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses_metr…
- [Dynamic View Synthesis from Dynamic Monocular Video](papers/dynamic-view-synthesis-from-dynamic-monocular-video.html): - **addresses** → Novel View Synthesis _(Task)_ - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses_metric** → LPIPS _(Metric)_ - **uses_metric** → PSNR _(Metric)_ - **uses_metric** → SSIM _(Metric)_
- [Feature 3DGS: Supercharging 3D Gaussian Splatting to Enable Distilled Feature Fields](papers/feature-3dgs-supercharging-3d-gaussian-splatting-to-enable-distilled-feature-fields.html): - **addresses** → Novel View Synthesis _(Task)_ - **belongs_to_approach_family** → Gaussian Splatting Reconstruction _(ApproachFamily)_ - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses** → CLIP _(Model)_ - **uses*…
- [GALA3D: Towards Text-to-3D Complex Scene Generation via Layout-guided Generative Gaussian Splatting](papers/gala3d-towards-text-to-3d-complex-scene-generation-via-layout-guided-generative-4a4374ee.html): - **belongs_to_approach_family** → Gaussian Splatting Reconstruction _(ApproachFamily)_ - **introduces** → GALA3D _(Algorithm)_ - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses** → Gaussian Splatting _(Methodologi…
- [Gaussian Splatting SLAM](papers/gaussian-splatting-slam.html): - **addresses** → Novel View Synthesis _(Task)_ - **addresses** → Visual SLAM _(ResearchTopic)_ - **belongs_to_approach_family** → Gaussian Splatting Reconstruction _(ApproachFamily)_ - **part_of** → 3D/4D Vision and Reconstruction _(Resea…
- [GS-SLAM: Dense Visual SLAM with 3D Gaussian Splatting](papers/gs-slam-dense-visual-slam-with-3d-gaussian-splatting.html): - **addresses** → Visual SLAM _(ResearchTopic)_ - **belongs_to_approach_family** → Gaussian Splatting Reconstruction _(ApproachFamily)_ - **evaluated_on** → Replica _(Benchmark)_ - **part_of** → 3D/4D Vision and Reconstruction _(ResearchFi…
- [HyperNeRF: A Higher-Dimensional Representation for Topologically Varying Neural Radiance Fields](papers/hypernerf-a-higher-dimensional-representation-for-topologically-varying-neural-radiance-fields.html): - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses_metric** → LPIPS _(Metric)_
- [Image Generators are Generalist Vision Learners](papers/image-generators-are-generalist-vision-learners.html): - **implemented_in** → GitHub 분석: google-research/vision-banana _(Repository)_ - **part_of** → Research Literature _(ResearchField)_ - **uses** → Segment Anything _(Model)_
- [Implicit Geometric Regularization for Learning Shapes](papers/implicit-geometric-regularization-for-learning-shapes.html): - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **part_of** → Research Literature _(ResearchField)_ - **uses** → Point Cloud _(TechnicalTerm)_ - **uses_metric** → LPIPS _(Metric)_ - **uses_metric** → PSNR _(Metric)_ - *…
- [Instant Neural Graphics Primitives with a Multiresolution Hash Encoding](papers/instant-neural-graphics-primitives-with-a-multiresolution-hash-encoding.html): - **implemented_in** → About NVlabs/instant-ngp _(Repository)_ - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **part_of** → Research Literature _(ResearchField)_ - **uses_metric** → LPIPS _(Metric)_ - **uses_metric** →…
- [Instant3D: Fast Text-to-3D with Sparse-View Generation and Large Reconstruction Model](papers/instant3d-fast-text-to-3d-with-sparse-view-generation-and-large-reconstruction-model.html): - **introduces** → Instant3D _(Algorithm)_ - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses_metric** → LPIPS _(Metric)_ - **uses_metric** → PSNR _(Metric)_ - **uses_metric** → SSIM _(Metric)_
- [K-Planes: Explicit Radiance Fields in Space, Time, and Appearance](papers/k-planes-explicit-radiance-fields-in-space-time-and-appearance.html): - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses_metric** → LPIPS _(Metric)_ - **uses_metric** → PSNR _(Metric)_ - **uses_metric** → SSIM _(Metric)_
- [latentSplat: Autoencoding Variational Gaussians for Fast Generalizable 3D Reconstruction](papers/latentsplat-autoencoding-variational-gaussians-for-fast-generalizable-3d-reconstruction.html): - **belongs_to_approach_family** → Gaussian Splatting Reconstruction _(ApproachFamily)_ - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses** → Gaussian Splatting _(MethodologicalConcept)_ - **uses** → Multi-View Con…
- [LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation](papers/lgm-large-multi-view-gaussian-model-for-high-resolution-3d-content-creation.html): - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses** → Volumetric Rendering _(MethodologicalConcept)_ - **uses_metric** → LPIPS _(Metric)_ - **uses_metric** → PSNR _(Metric)_ - **uses_metric** → SSIM _(Metric)_
- [LRM: Large Reconstruction Model for Single Image to 3D](papers/lrm-large-reconstruction-model-for-single-image-to-3d.html): - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses_dataset** → Objaverse _(Dataset)_ - **uses_dataset** → ShapeNet _(Dataset)_ - **uses_metric** → LPIPS _(Metric)_ - **uses_metric** → PSNR _(Metric)_ - **uses_metric…
- [LucidDreamer: Domain-free Generation of 3D Gaussian Splatting Scenes](papers/luciddreamer-domain-free-generation-of-3d-gaussian-splatting-scenes.html): - **belongs_to_approach_family** → Gaussian Splatting Reconstruction _(ApproachFamily)_ - **introduces** → LucidDreamer _(Algorithm)_ - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses** → Depth Map _(TechnicalTerm)…
- [Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors](papers/magic123-one-image-to-high-quality-3d-object-generation-using-both-2d-and-3d-diffusion-priors.html): - **addresses** → Image-to-3D _(Task)_ - **introduces** → Magic123 _(Algorithm)_ - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses** → Volumetric Rendering _(MethodologicalConcept)_ - **uses_dataset** → ShapeNet _(…
- [Magic3D: High-Resolution Text-to-3D Content Creation](papers/magic3d-high-resolution-text-to-3d-content-creation.html): - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses_metric** → LPIPS _(Metric)_ - **uses_metric** → PSNR _(Metric)_ - **uses_metric** → SSIM _(Metric)_
- [Mathematical Supplement for the $\\\\texttt{gsplat}$ Library](papers/mathematical-supplement-for-the-texttt-gsplat-library.html): - **addresses** → Visual SLAM _(ResearchTopic)_ - **belongs_to_approach_family** → Gaussian Splatting Reconstruction _(ApproachFamily)_ - **implemented_in** → About nerfstudio-project/gsplat _(Repository)_ - **part_of** → 3D/4D Vision and…
- [MERF: Memory-Efficient Radiance Fields for Real-time View Synthesis in Unbounded Scenes](papers/merf-memory-efficient-radiance-fields-for-real-time-view-synthesis-in-unbounded-scenes.html): - **evaluated_on** → Mip-NeRF 360 _(Benchmark)_ - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **part_of** → Research Literature _(ResearchField)_ - **uses** → Volumetric Rendering _(MethodologicalConcept)_ - **uses_me…
- [Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fields](papers/mip-nerf-360-unbounded-anti-aliased-neural-radiance-fields.html): - **belongs_to_approach_family** → Gaussian Splatting Reconstruction _(ApproachFamily)_ - **evaluated_on** → Mip-NeRF 360 _(Benchmark)_ - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **part_of** → Research Literature _…
- [Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields](papers/mip-nerf-a-multiscale-representation-for-anti-aliasing-neural-radiance-fields.html): - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **part_of** → Research Literature _(ResearchField)_ - **uses_dataset** → NeRF Synthetic _(Dataset)_ - **uses_metric** → Accuracy _(Metric)_ - **uses_metric** → LPIPS _(Met…
- [MonoSDF: Exploring Monocular Geometric Cues for Neural Implicit Surface Reconstruction](papers/monosdf-exploring-monocular-geometric-cues-for-neural-implicit-surface-reconstruction.html): - **evaluated_on** → Replica _(Benchmark)_ - **evaluated_on** → ScanNet _(Benchmark)_ - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses_metric** → LPIPS _(Metric)_ - **uses_metric** → PSNR _(Metric)_ - **uses_metri…
- [MVSplat: Efficient 3D Gaussian Splatting from Sparse Multi-View Images](papers/mvsplat-efficient-3d-gaussian-splatting-from-sparse-multi-view-images.html): - **belongs_to_approach_family** → Gaussian Splatting Reconstruction _(ApproachFamily)_ - **introduces** → MVSplat _(Algorithm)_ - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses** → Gaussian Splatting _(Methodolog…
- [NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections](papers/nerf-in-the-wild-neural-radiance-fields-for-unconstrained-photo-collections.html): - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **part_of** → Research Literature _(ResearchField)_ - **uses_metric** → LPIPS _(Metric)_ - **uses_metric** → PSNR _(Metric)_ - **uses_metric** → SSIM _(Metric)_
- [NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis](papers/nerf-representing-scenes-as-neural-radiance-fields-for-view-synthesis.html): - **implemented_in** → About bmild/nerf _(Repository)_ - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses** → Volumetric Rendering _(MethodologicalConcept)_ - **uses_dataset** → LLFF _(Dataset)_ - **uses_metric** →…
- [Nerfies: Deformable Neural Radiance Fields](papers/nerfies-deformable-neural-radiance-fields.html): - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses** → Volumetric Rendering _(MethodologicalConcept)_ - **uses_metric** → LPIPS _(Metric)_ - **uses_metric** → PSNR _(Metric)_ - **uses_metric** → SSIM _(Metric)_
- [NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction](papers/neus-learning-neural-implicit-surfaces-by-volume-rendering-for-multi-view-reconstruction.html): - **addresses** → Novel View Synthesis _(Task)_ - **evaluated_on** → DTU _(Benchmark)_ - **implemented_in** → About Totoro97/NeuS _(Repository)_ - **introduces** → NeuS _(Algorithm)_ - **part_of** → 3D/4D Vision and Reconstruction _(Resear…
- [NICE-SLAM: Neural Implicit Scalable Encoding for SLAM](papers/nice-slam-neural-implicit-scalable-encoding-for-slam.html): - **addresses** → Visual SLAM _(ResearchTopic)_ - **evaluated_on** → Replica _(Benchmark)_ - **evaluated_on** → ScanNet _(Benchmark)_ - **introduces** → NICE-SLAM _(Algorithm)_ - **part_of** → 3D/4D Vision and Reconstruction _(ResearchFiel…
- [PlenOctrees for Real-time Rendering of Neural Radiance Fields](papers/plenoctrees-for-real-time-rendering-of-neural-radiance-fields.html): - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses** → Fine-tuning _(TrainingParadigm)_
- [Plenoxels: Radiance Fields without Neural Networks](papers/plenoxels-radiance-fields-without-neural-networks.html): - **implemented_in** → About sxyu/svox2 _(Repository)_ - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses_dataset** → NeRF Synthetic _(Dataset)_ - **uses_metric** → LPIPS _(Metric)_ - **uses_metric** → PSNR _(Metric…
- [Point-SLAM: Dense Neural Point Cloud-based SLAM](papers/point-slam-dense-neural-point-cloud-based-slam.html): - **addresses** → Visual SLAM _(ResearchTopic)_ - **belongs_to_approach_family** → Gaussian Splatting Reconstruction _(ApproachFamily)_ - **evaluated_on** → Replica _(Benchmark)_ - **evaluated_on** → ScanNet _(Benchmark)_ - **part_of** → 3…
- [ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation](papers/prolificdreamer-high-fidelity-and-diverse-text-to-3d-generation-with-variational-2853a4ed.html): - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses** → Fine-tuning _(TrainingParadigm)_ - **uses_metric** → LPIPS _(Metric)_ - **uses_metric** → PSNR _(Metric)_ - **uses_metric** → SSIM _(Metric)_
- [Revising Densification in Gaussian Splatting](papers/revising-densification-in-gaussian-splatting.html): - **addresses** → Novel View Synthesis _(Task)_ - **belongs_to_approach_family** → Gaussian Splatting Reconstruction _(ApproachFamily)_ - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses** → Gaussian Splatting _(Met…
- [Scaffold-GS: Structured 3D Gaussians for View-Adaptive Rendering](papers/scaffold-gs-structured-3d-gaussians-for-view-adaptive-rendering.html): - **belongs_to_approach_family** → Gaussian Splatting Reconstruction _(ApproachFamily)_ - **introduces** → Scaffold-GS _(Algorithm)_ - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses** → Gaussian Splatting _(Method…
- [SuGaR: Surface-Aligned Gaussian Splatting for Efficient 3D Mesh Reconstruction and High-Quality Mesh Rendering](papers/sugar-surface-aligned-gaussian-splatting-for-efficient-3d-mesh-reconstruction-an-30733ba4.html): - **belongs_to_approach_family** → Gaussian Splatting Reconstruction _(ApproachFamily)_ - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses** → Gaussian Splatting _(MethodologicalConcept)_ - **uses_metric** → LPIPS _…
- [TripoSR: Fast 3D Object Reconstruction from a Single Image](papers/triposr-fast-3d-object-reconstruction-from-a-single-image.html): - **addresses** → Image-to-3D _(Task)_ - **implemented_in** → About VAST-AI-Research/TripoSR _(Repository)_ - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses** → Volumetric Rendering _(MethodologicalConcept)_ - **u…
- [UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for Multi-View Reconstruction](papers/unisurf-unifying-neural-implicit-surfaces-and-radiance-fields-for-multi-view-reconstruction.html): - **addresses** → Novel View Synthesis _(Task)_ - **evaluated_on** → DTU _(Benchmark)_ - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **part_of** → Research Literature _(ResearchField)_ - **uses_metric** → LPIPS _(Metr…
- [Volume Rendering of Neural Implicit Surfaces](papers/volume-rendering-of-neural-implicit-surfaces.html): - **part_of** → 3D/4D Vision and Reconstruction _(ResearchField)_ - **uses_metric** → LPIPS _(Metric)_ - **uses_metric** → PSNR _(Metric)_ - **uses_metric** → SSIM _(Metric)_
- [Zero-1-to-3: Zero-shot One Image to 3D Object](papers/zero-1-to-3-zero-shot-one-image-to-3d-object.html): - **addresses** → Image-to-3D _(Task)_ - **addresses** → Novel View Synthesis _(Task)_ - **implemented_in** → About cvlab-columbia/zero123 _(Repository)_ - **introduces** → Zero-1-to-3 _(Algorithm)_ - **part_of** → 3D/4D Vision and Reconst…

## Repos

- [About ashawkey/stable-dreamfusion](repos/about-ashawkey-stable-dreamfusion.html): - **mentioned_in** → DreamFusion: Text-to-3D using 2D Diffusion _(Paper)_ - **uses_metric** → Precision _(Metric)_
- [About bmild/nerf](repos/about-bmild-nerf.html): - **evaluated_on** → Mip-NeRF 360 _(Benchmark)_ - **mentioned_in** → NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis _(Paper)_ - **uses_dataset** → Blender _(Dataset)_ - **uses_dataset** → LLFF _(Dataset)_
- [About cvlab-columbia/zero123](repos/about-cvlab-columbia-zero123.html): - **documents** → Novel View Synthesis _(Task)_ - **mentioned_in** → Zero-1-to-3: Zero-shot One Image to 3D Object _(Paper)_ - **uses_dataset** → Objaverse _(Dataset)_ - **uses_metric** → Accuracy _(Metric)_
- [About dreamgaussian/dreamgaussian](repos/about-dreamgaussian-dreamgaussian.html): - **mentioned_in** → DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation _(Paper)_
- [About graphdeco-inria/gaussian-splatting](repos/about-graphdeco-inria-gaussian-splatting.html): - **evaluated_on** → Tanks and Temples _(Benchmark)_ - **mentioned_in** → 3D Gaussian Splatting for Real-Time Radiance Field Rendering _(Paper)_ - **uses_dataset** → NeRF Synthetic _(Dataset)_ - **uses_metric** → PSNR _(Metric)_ - **uses_m…
- [About hustvl/4DGaussians](repos/about-hustvl-4dgaussians.html): - **mentioned_in** → 4D Gaussian Splatting for Real-Time Dynamic Scene Rendering _(Paper)_ - **uses_dataset** → Blender _(Dataset)_ - **uses_dataset** → LLFF _(Dataset)_
- [About nerfstudio-project/gsplat](repos/about-nerfstudio-project-gsplat.html): - **mentioned_in** → Mathematical Supplement for the $\\texttt{gsplat}$ Library _(Paper)_ - **uses_metric** → LPIPS _(Metric)_ - **uses_metric** → PSNR _(Metric)_ - **uses_metric** → SSIM _(Metric)_
- [About NVlabs/instant-ngp](repos/about-nvlabs-instant-ngp.html): - **mentioned_in** → Instant Neural Graphics Primitives with a Multiresolution Hash Encoding _(Paper)_ - **uses_metric** → mAP _(Metric)_
- [About princeton-vl/DROID-SLAM](repos/about-princeton-vl-droid-slam.html): - **mentioned_in** → DROID-SLAM: Deep Visual SLAM for Monocular, Stereo, and RGB-D Cameras _(Paper)_
- [About sxyu/svox2](repos/about-sxyu-svox2.html): - **evaluated_on** → Mip-NeRF 360 _(Benchmark)_ - **evaluated_on** → Tanks and Temples _(Benchmark)_ - **mentioned_in** → Plenoxels: Radiance Fields without Neural Networks _(Paper)_ - **uses_dataset** → Blender _(Dataset)_ - **uses_datase…
- [About Totoro97/NeuS](repos/about-totoro97-neus.html): - **evaluated_on** → DTU _(Benchmark)_ - **mentioned_in** → NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction _(Paper)_
- [About VAST-AI-Research/TripoSR](repos/about-vast-ai-research-triposr.html): - **mentioned_in** → TripoSR: Fast 3D Object Reconstruction from a Single Image _(Paper)_
- [Federation semantic-link eval](repos/federation-semantic-link-eval.html): - **reports_result** → F1=0.00 _(Result)_ - **reports_result** → F1=0.82 _(Result)_ - **reports_result** → precision=1.00 _(Result)_ - **reports_result** → recall=0.70 _(Result)_ - **uses_metric** → F1 _(Metric)_ - **uses_metric** → Precis…
- [GitHub 분석: genforce/JOSH](repos/github-분석-genforce-josh.html)
- [GitHub 분석: google-research/vision-banana](repos/github-분석-google-research-vision-banana.html): - **implemented_in** → Image Generators are Generalist Vision Learners _(Paper)_

## Concepts

- [4D Gaussian Splatting](concepts/4d-gaussian-splatting.html): - **uses** → 4D Gaussian Splatting for Real-Time Dynamic Scene Rendering _(Paper)_ - **uses** → 4D-Rotor Gaussian Splatting: Towards Efficient Novel View Synthesis for Dynamic Scenes _(Paper)_ - **uses** → Dynamic Gaussian Splatting _(Appr…
- [Co-SLAM](concepts/co-slam.html): - **introduces** → Co-SLAM: Joint Coordinate and Sparse Parametric Encodings for Neural Real-Time SLAM _(Paper)_
- [DeepV2D](concepts/deepv2d.html): - **introduces** → DeepV2D: Video to Depth with Differentiable Structure from Motion _(Paper)_
- [Depth Map](concepts/depth-map.html): - **uses** → 2D Gaussian Splatting for Geometrically Accurate Radiance Fields _(Paper)_ - **uses** → LucidDreamer: Domain-free Generation of 3D Gaussian Splatting Scenes _(Paper)_ - **uses** → Mip-NeRF 360: Unbounded Anti-Aliased Neural Ra…
- [DreamGaussian](concepts/dreamgaussian.html): - **introduces** → DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation _(Paper)_
- [DROID-SLAM](concepts/droid-slam.html): - **introduces** → DROID-SLAM: Deep Visual SLAM for Monocular, Stereo, and RGB-D Cameras _(Paper)_
- [Fine-tuning](concepts/fine-tuning.html): - **uses** → DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation _(Paper)_ - **uses** → PlenOctrees for Real-time Rendering of Neural Radiance Fields _(Paper)_ - **uses** → ProlificDreamer: High-Fidelity and Dive…
- [GALA3D](concepts/gala3d.html): - **introduces** → GALA3D: Towards Text-to-3D Complex Scene Generation via Layout-guided Generative Gaussian Splatting _(Paper)_
- [Gaussian Splatting](concepts/gaussian-splatting.html): - **uses** → 2D Gaussian Splatting for Geometrically Accurate Radiance Fields _(Paper)_ - **uses** → 3D Gaussian Splatting for Real-Time Radiance Field Rendering _(Paper)_ - **uses** → 4D Gaussian Splatting for Real-Time Dynamic Scene Rend…
- [Image-to-3D](concepts/image-to-3d.html): - **addresses** → Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors _(Paper)_ - **addresses** → TripoSR: Fast 3D Object Reconstruction from a Single Image _(Paper)_ - **addresses** → Zero-1-to-3…
- [Instant3D](concepts/instant3d.html): - **introduces** → Instant3D: Fast Text-to-3D with Sparse-View Generation and Large Reconstruction Model _(Paper)_
- [LucidDreamer](concepts/luciddreamer.html): - **introduces** → LucidDreamer: Domain-free Generation of 3D Gaussian Splatting Scenes _(Paper)_
- [Magic123](concepts/magic123.html): - **introduces** → Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors _(Paper)_
- [Multi-View Consistency](concepts/multi-view-consistency.html): - **uses** → latentSplat: Autoencoding Variational Gaussians for Fast Generalizable 3D Reconstruction _(Paper)_
- [MVSplat](concepts/mvsplat.html): - **introduces** → MVSplat: Efficient 3D Gaussian Splatting from Sparse Multi-View Images _(Paper)_
- [NeuS](concepts/neus.html): - **introduces** → NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction _(Paper)_
- [NICE-SLAM](concepts/nice-slam.html): - **introduces** → NICE-SLAM: Neural Implicit Scalable Encoding for SLAM _(Paper)_
- [Novel View Synthesis](concepts/novel-view-synthesis.html): Registered term referenced in cvlab-columbia/zero123
- [Point Cloud](concepts/point-cloud.html): - **uses** → GALA3D: Towards Text-to-3D Complex Scene Generation via Layout-guided Generative Gaussian Splatting _(Paper)_ - **uses** → Implicit Geometric Regularization for Learning Shapes _(Paper)_ - **uses** → LucidDreamer: Domain-free…
- [Pre-training](concepts/pre-training.html): - **uses** → Zero-1-to-3: Zero-shot One Image to 3D Object _(Paper)_
- [Scaffold-GS](concepts/scaffold-gs.html): - **introduces** → Scaffold-GS: Structured 3D Gaussians for View-Adaptive Rendering _(Paper)_
- [Volumetric Rendering](concepts/volumetric-rendering.html): - **uses** → 2D Gaussian Splatting for Geometrically Accurate Radiance Fields _(Paper)_ - **uses** → 3D Gaussian Splatting for Real-Time Radiance Field Rendering _(Paper)_ - **uses** → LGM: Large Multi-View Gaussian Model for High-Resoluti…
- [Zero-1-to-3](concepts/zero-1-to-3.html): - **introduces** → Zero-1-to-3: Zero-shot One Image to 3D Object _(Paper)_

## Entities

- [Accuracy](entities/accuracy.html): - **uses_metric** → About cvlab-columbia/zero123 _(Repository)_ - **uses_metric** → Co-SLAM: Joint Coordinate and Sparse Parametric Encodings for Neural Real-Time SLAM _(Paper)_ - **uses_metric** → DROID-SLAM: Deep Visual SLAM for Monocula…
- [Blender](entities/blender.html): - **uses_dataset** → About bmild/nerf _(Repository)_ - **uses_dataset** → About hustvl/4DGaussians _(Repository)_ - **uses_dataset** → About sxyu/svox2 _(Repository)_ - **uses_dataset** → BARF: Bundle-Adjusting Neural Radiance Fields _(Pap…
- [CLIP](entities/clip.html): - **uses** → Feature 3DGS: Supercharging 3D Gaussian Splatting to Enable Distilled Feature Fields _(Paper)_
- [DTU](entities/dtu.html): - **evaluated_on** → About Totoro97/NeuS _(Repository)_ - **evaluated_on** → NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction _(Paper)_ - **evaluated_on** → UNISURF: Unifying Neural Implicit Surface…
- [F1](entities/f1.html): - **uses_metric** → CLI Redesign Implementation Plan (v0.6.0 _(SourceDocument)_ - **uses_metric** → F1=0.00 _(Result)_ - **uses_metric** → F1=0.82 _(Result)_ - **uses_metric** → Federation semantic-link eval _(Repository)_
- [F1=0.00](entities/f1-0-00.html): F1 = 0.00
- [F1=0.82](entities/f1-0-82.html): F1=0.82
- [LLFF](entities/llff.html): - **uses_dataset** → About bmild/nerf _(Repository)_ - **uses_dataset** → About hustvl/4DGaussians _(Repository)_ - **uses_dataset** → About sxyu/svox2 _(Repository)_ - **uses_dataset** → NeRF: Representing Scenes as Neural Radiance Fields…
- [LPIPS](entities/lpips.html): - **uses_metric** → 2D Gaussian Splatting for Geometrically Accurate Radiance Fields _(Paper)_ - **uses_metric** → AGG: Amortized Generative 3D Gaussians for Single Image to 3D _(Paper)_ - **uses_metric** → About nerfstudio-project/gsplat…
- [mAP](entities/map.html): - **uses_metric** → 2D Gaussian Splatting for Geometrically Accurate Radiance Fields _(Paper)_ - **uses_metric** → About NVlabs/instant-ngp _(Repository)_ - **uses_metric** → Activity Summary + Citation-Name Fix — Design _(SourceDocument)_…
- [MATH](entities/math.html): - **evaluated_on** → Distillery — layered per-agent knowledge graphs _(SourceDocument)_
- [Mip-NeRF 360](entities/mip-nerf-360.html): - **evaluated_on** → About bmild/nerf _(Repository)_ - **evaluated_on** → About sxyu/svox2 _(Repository)_ - **evaluated_on** → Demo corpus licenses _(SourceDocument)_ - **evaluated_on** → MERF: Memory-Efficient Radiance Fields for Real-tim…
- [NeRF Synthetic](entities/nerf-synthetic.html): - **uses_dataset** → About graphdeco-inria/gaussian-splatting _(Repository)_ - **uses_dataset** → Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields _(Paper)_ - **uses_dataset** → Plenoxels: Radiance Fields with…
- [Objaverse](entities/objaverse.html): - **uses_dataset** → About cvlab-columbia/zero123 _(Repository)_ - **uses_dataset** → LRM: Large Reconstruction Model for Single Image to 3D _(Paper)_ - **uses_dataset** → Zero-1-to-3: Zero-shot One Image to 3D Object _(Paper)_
- [Precision](entities/precision.html): - **uses_metric** → About ashawkey/stable-dreamfusion _(Repository)_ - **uses_metric** → Cross-project federated graph mode — design sketch _(SourceDocument)_ - **uses_metric** → Federation semantic-link eval _(Repository)_ - **uses_metric…
- [precision=1.00](entities/precision-1-00.html): precision=1.00
- [PSNR](entities/psnr.html): - **uses_metric** → 2D Gaussian Splatting for Geometrically Accurate Radiance Fields _(Paper)_ - **uses_metric** → AGG: Amortized Generative 3D Gaussians for Single Image to 3D _(Paper)_ - **uses_metric** → About graphdeco-inria/gaussian-s…
- [Recall](entities/recall.html): - **uses_metric** → AgentRunbook-style multi-granularity memory for Tesserae _(SourceDocument)_ - **uses_metric** → Claude Code plugin _(SourceDocument)_ - **uses_metric** → Cross-project federated graph mode — design sketch _(SourceDocume…
- [recall=0.70](entities/recall-0-70.html): recall=0.70
- [recall=7](entities/recall-7.html): recall 7
- [Replica](entities/replica.html): - **evaluated_on** → Co-SLAM: Joint Coordinate and Sparse Parametric Encodings for Neural Real-Time SLAM _(Paper)_ - **evaluated_on** → GS-SLAM: Dense Visual SLAM with 3D Gaussian Splatting _(Paper)_ - **evaluated_on** → MonoSDF: Exploring…
- [SAM](entities/sam.html): - **uses** → Feature 3DGS: Supercharging 3D Gaussian Splatting to Enable Distilled Feature Fields _(Paper)_
- [ScanNet](entities/scannet.html): - **evaluated_on** → Co-SLAM: Joint Coordinate and Sparse Parametric Encodings for Neural Real-Time SLAM _(Paper)_ - **evaluated_on** → MonoSDF: Exploring Monocular Geometric Cues for Neural Implicit Surface Reconstruction _(Paper)_ - **ev…
- [Segment Anything](entities/segment-anything.html): - **uses** → Feature 3DGS: Supercharging 3D Gaussian Splatting to Enable Distilled Feature Fields _(Paper)_ - **uses** → Image Generators are Generalist Vision Learners _(Paper)_
- [ShapeNet](entities/shapenet.html): - **uses_dataset** → LRM: Large Reconstruction Model for Single Image to 3D _(Paper)_ - **uses_dataset** → Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors _(Paper)_
- [SSIM](entities/ssim.html): - **uses_metric** → 2D Gaussian Splatting for Geometrically Accurate Radiance Fields _(Paper)_ - **uses_metric** → AGG: Amortized Generative 3D Gaussians for Single Image to 3D _(Paper)_ - **uses_metric** → About graphdeco-inria/gaussian-s…
- [Stable Diffusion](entities/stable-diffusion.html): - **uses** → Zero-1-to-3: Zero-shot One Image to 3D Object _(Paper)_
- [Tanks and Temples](entities/tanks-and-temples.html): - **evaluated_on** → About graphdeco-inria/gaussian-splatting _(Repository)_ - **evaluated_on** → About sxyu/svox2 _(Repository)_
- [top-1](entities/top-1.html): - **uses_metric** → top-1=0 _(Result)_ - **uses_metric** → top-1=2 _(Result)_
- [top-1=0](entities/top-1-0.html): top-10
- [top-1=2](entities/top-1-2.html): top-12

## Topics

- [3D/4D Vision and Reconstruction](topics/3d-4d-vision-and-reconstruction.html): - **part_of** → 2D Gaussian Splatting for Geometrically Accurate Radiance Fields _(Paper)_ - **part_of** → 3D Gaussian Splatting for Real-Time Radiance Field Rendering _(Paper)_ - **part_of** → 4D Gaussian Splatting for Real-Time Dynamic S…
- [Dynamic Gaussian Splatting](topics/dynamic-gaussian-splatting.html): - **uses** → 4D Gaussian Splatting _(MethodologicalConcept)_
- [Gaussian Splatting Reconstruction](topics/gaussian-splatting-reconstruction.html): - **uses** → Gaussian Splatting _(MethodologicalConcept)_
- [Research Literature](topics/research-literature.html): - **part_of** → Image Generators are Generalist Vision Learners _(Paper)_ - **part_of** → Implicit Geometric Regularization for Learning Shapes _(Paper)_ - **part_of** → Instant Neural Graphics Primitives with a Multiresolution Hash Encodi…
- [Visual SLAM](topics/visual-slam.html): - **addresses** → 3D Gaussian Splatting for Real-Time Radiance Field Rendering _(Paper)_ - **addresses** → BARF: Bundle-Adjusting Neural Radiance Fields _(Paper)_ - **addresses** → Co-SLAM: Joint Coordinate and Sparse Parametric Encodings…

## Syntheses

- [Comparison — Dynamic Gaussian Splatting vs Gaussian Splatting Reconstruction](syntheses/compare-dynamic-gaussian-splatting-vs-gaussian-splatting-reconstruction.html): Both approach families connect to `Novel View Synthesis` (Task).
- [Daily Digest — 2026-04-25](syntheses/daily-2026-04-25.html): Sources ingested under `data/research/daily/2026-04-25/`.
- [Daily Digest — 2026-04-26](syntheses/daily-2026-04-26.html): Sources ingested under `data/research/daily/2026-04-26/`.
- [Field Overview — 3D/4D Vision and Reconstruction](syntheses/field-3d-4d-vision-and-reconstruction.html): Dynamic Gaussian Splatting (ApproachFamily) — 2 contributing paper(s) connect to this thread.
- [Field Overview — Research Literature](syntheses/field-research-literature.html): Gaussian Splatting Reconstruction (ApproachFamily) — 20 contributing paper(s) connect to this thread.
- [Project Pulse](syntheses/pulse.html): Snapshot of the wiki at the most recent compile.
- [Topic — Gaussian Splatting Reconstruction](syntheses/topic-gaussian-splatting-reconstruction.html): Type: ApproachFamily.
- [Topic — Visual SLAM](syntheses/topic-visual-slam.html): Type: ResearchTopic.
- [Weekly Synthesis — 2026-W17](syntheses/weekly-2026-W17.html): Coverage of `data/research/weekly/2026-W17/`.

## Questions

- [Does dynamic reconstruction work at minute-scale capture in the wild?](questions/does-dynamic-reconstruction-work-at-minute-scale-capture-in-the-wild.html)
- [Feed-forward reconstruction vs per-scene optimisation: where does each win?](questions/feed-forward-reconstruction-vs-per-scene-optimisation-where-does-each-win.html)
- [How robust is multi-view consistency under fast camera motion?](questions/how-robust-is-multi-view-consistency-under-fast-camera-motion.html)