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LICENSES.md

examples/demo-corpus/LICENSES.md

Demo corpus licenses

Every external source mirrored into examples/demo-corpus/ is listed here with its origin URL, license, and inclusion justification. Sources that aren't on this list aren't in the corpus.

Last updated: 2026-05-15. Compiled by the Phase 1 corpus author.

arXiv paper abstracts (CC0 / public domain)

Per arXiv's policy, abstracts displayed on arXiv abstract pages are not subject to copyright (CC0-equivalent / public domain). The corpus mirrors 50 abstracts verbatim. Each data/research/papers/<slug>/abstract.md carries license: CC0 (arXiv abstract) in its frontmatter and a > Verbatim CC0 abstract mirrored from arXiv quote block.

#arXiv idTitleFirst authorYearSub-topic
12308.040793D Gaussian Splatting for Real-Time Radiance Field RenderingKerbl20233D Gaussian Splatting
22403.178882D Gaussian Splatting for Geometrically Accurate Radiance FieldsHuang20243D Gaussian Splatting
32401.04099AGG: Amortized Generative 3D Gaussians for Single Image to 3DXu20243D Gaussian Splatting
42312.02121Mathematical Supplement for the $\texttt{gsplat}$ LibraryYe20233D Gaussian Splatting
52312.00109Scaffold-GS: Structured 3D Gaussians for View-Adaptive RenderingLu20233D Gaussian Splatting
62403.14627MVSplat: Efficient 3D Gaussian Splatting from Sparse Multi-View ImagesChen20243D Gaussian Splatting
72402.07207GALA3D: Towards Text-to-3D Complex Scene Generation via Layout-guid...Zhou20243D Gaussian Splatting
82311.13384LucidDreamer: Domain-free Generation of 3D Gaussian Splatting ScenesChung20233D Gaussian Splatting
92312.03203Feature 3DGS: Supercharging 3D Gaussian Splatting to Enable Distill...Zhou20233D Gaussian Splatting
102403.16292latentSplat: Autoencoding Variational Gaussians for Fast Generaliza...Wewer20243D Gaussian Splatting
112404.06109Revising Densification in Gaussian SplattingBulò20243D Gaussian Splatting
122311.12775SuGaR: Surface-Aligned Gaussian Splatting for Efficient 3D Mesh Rec...Guédon20233D Gaussian Splatting
132003.08934NeRF: Representing Scenes as Neural Radiance Fields for View SynthesisMildenhall2020Neural Radiance Fields
142103.13415Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radi...Barron2021Neural Radiance Fields
152111.12077Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance FieldsBarron2021Neural Radiance Fields
162201.05989Instant Neural Graphics Primitives with a Multiresolution Hash Enco...Müller2022Neural Radiance Fields
172112.05131Plenoxels: Radiance Fields without Neural NetworksYu2021Neural Radiance Fields
182301.10241K-Planes: Explicit Radiance Fields in Space, Time, and AppearanceFridovich-Keil2023Neural Radiance Fields
192302.12249MERF: Memory-Efficient Radiance Fields for Real-time View Synthesis...Reiser2023Neural Radiance Fields
202008.02268NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Co...Martin-Brualla2020Neural Radiance Fields
212104.06405BARF: Bundle-Adjusting Neural Radiance FieldsLin2021Neural Radiance Fields
222103.14024PlenOctrees for Real-time Rendering of Neural Radiance FieldsYu2021Neural Radiance Fields
231607.02565Direct Sparse OdometryEngel2016Visual SLAM and MVS
242108.10869DROID-SLAM: Deep Visual SLAM for Monocular, Stereo, and RGB-D CamerasTeed2021Visual SLAM and MVS
252112.12130NICE-SLAM: Neural Implicit Scalable Encoding for SLAMZhu2021Visual SLAM and MVS
262304.14377Co-SLAM: Joint Coordinate and Sparse Parametric Encodings for Neura...Wang2023Visual SLAM and MVS
272311.11700GS-SLAM: Dense Visual SLAM with 3D Gaussian SplattingYan2023Visual SLAM and MVS
282312.06741Gaussian Splatting SLAMMatsuki2023Visual SLAM and MVS
292304.04278Point-SLAM: Dense Neural Point Cloud-based SLAMSandström2023Visual SLAM and MVS
301812.04605DeepV2D: Video to Depth with Differentiable Structure from MotionTeed2018Visual SLAM and MVS
312209.14988DreamFusion: Text-to-3D using 2D DiffusionPoole2022Diffusion-based 3D Generation
322211.10440Magic3D: High-Resolution Text-to-3D Content CreationLin2022Diffusion-based 3D Generation
332303.11328Zero-1-to-3: Zero-shot One Image to 3D ObjectLiu2023Diffusion-based 3D Generation
342305.16213ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation wi...Wang2023Diffusion-based 3D Generation
352309.16653DreamGaussian: Generative Gaussian Splatting for Efficient 3D Conte...Tang2023Diffusion-based 3D Generation
362306.17843Magic123: One Image to High-Quality 3D Object Generation Using Both...Qian2023Diffusion-based 3D Generation
372106.10689NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Mul...Wang2021Mesh and Surface Reconstruction
382106.12052Volume Rendering of Neural Implicit SurfacesYariv2021Mesh and Surface Reconstruction
392002.10099Implicit Geometric Regularization for Learning ShapesGropp2020Mesh and Surface Reconstruction
402104.10078UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for ...Oechsle2021Mesh and Surface Reconstruction
412206.00665MonoSDF: Exploring Monocular Geometric Cues for Neural Implicit Sur...Yu2022Mesh and Surface Reconstruction
422011.12948Nerfies: Deformable Neural Radiance FieldsPark2020Dynamic and 4D Reconstruction
432106.13228HyperNeRF: A Higher-Dimensional Representation for Topologically Va...Park2021Dynamic and 4D Reconstruction
442105.06468Dynamic View Synthesis from Dynamic Monocular VideoGao2021Dynamic and 4D Reconstruction
452310.085284D Gaussian Splatting for Real-Time Dynamic Scene RenderingWu2023Dynamic and 4D Reconstruction
462402.033074D-Rotor Gaussian Splatting: Towards Efficient Novel View Synthesis...Duan2024Dynamic and 4D Reconstruction
472311.04400LRM: Large Reconstruction Model for Single Image to 3DHong2023Generative 3D Representations
482403.02151TripoSR: Fast 3D Object Reconstruction from a Single ImageTochilkin2024Generative 3D Representations
492402.05054LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content...Tang2024Generative 3D Representations
502311.06214Instant3D: Fast Text-to-3D with Sparse-View Generation and Large Re...Li2023Generative 3D Representations

OSS repository READMEs (Phase 3 mirror targets)

These repositories are referenced in Phase 1 frontmatter (oss_repo: field) and will have READMEs mirrored in Phase 3. They are listed here so the provenance audit is complete from Phase 1 onward.

Permissive licenses (MIT / Apache-2.0 / BSD) allow README redistribution with attribution. The corpus mirrors only the README files, not source code. The non-permissive licenses (Inria / NVIDIA research, custom) ship under research-only terms; including a short README mirror with attribution preserved and no code is treated as fair-use citation, but we flag the non-permissive status here so anyone forking the corpus is informed.

Phase 3 mirror picks (12 repos):

RepoLicenseURLJustification
graphdeco-inria/gaussian-splattingGaussian-Splatting License (research-only, non-commercial) (non-permissive — README mirror only)https://github.com/graphdeco-inria/gaussian-splattingCanonical 3D Gaussian Splatting reference implementation (Kerbl et al., 2308.04079).
nerfstudio-project/gsplatApache-2.0https://github.com/nerfstudio-project/gsplatOpen, permissive CUDA Gaussian splatting library used by Nerfstudio (paper: 2312.02121).
bmild/nerfMIThttps://github.com/bmild/nerfOriginal NeRF reference implementation (Mildenhall et al., 2003.08934).
NVlabs/instant-ngpNVIDIA Source Code License-NC (non-commercial research) (non-permissive — README mirror only)https://github.com/NVlabs/instant-ngpReference instant-NGP implementation (Müller et al., 2201.05989). Era-defining NeRF baseline.
sxyu/svox2BSD-2-Clausehttps://github.com/sxyu/svox2Plenoxels reference implementation (Yu et al., 2112.05131).
princeton-vl/DROID-SLAMBSD-3-Clausehttps://github.com/princeton-vl/DROID-SLAMDROID-SLAM reference implementation (Teed & Deng, 2108.10869).
Totoro97/NeuSMIThttps://github.com/Totoro97/NeuSNeuS reference implementation (Wang et al., 2106.10689).
cvlab-columbia/zero123MIThttps://github.com/cvlab-columbia/zero123Zero-1-to-3 reference implementation (Liu et al., 2303.11328).
ashawkey/stable-dreamfusionApache-2.0https://github.com/ashawkey/stable-dreamfusionWidely used open reimplementation of DreamFusion (paper: 2209.14988).
dreamgaussian/dreamgaussianMIThttps://github.com/dreamgaussian/dreamgaussianDreamGaussian reference implementation (Tang et al., 2309.16653).
VAST-AI-Research/TripoSRMIThttps://github.com/VAST-AI-Research/TripoSRTripoSR reference implementation (Tochilkin et al., 2403.02151).
hustvl/4DGaussiansApache-2.0https://github.com/hustvl/4DGaussians4D Gaussian Splatting reference (Wu et al., 2310.08528).

Additional OSS repos referenced from paper frontmatter (not all of these will have READMEs mirrored — listed here for full audit):

RepoLicenseURLJustification
hbb1/2d-gaussian-splattingInria/MPII research license (inherits from upstream 3DGS) (non-permissive)https://github.com/hbb1/2d-gaussian-splattingOfficial 2D Gaussian Splatting implementation (Huang et al., 2403.17888).
google/mipnerfApache-2.0https://github.com/google/mipnerfReference implementation of Mip-NeRF (Barron et al., 2103.13415).
sarafridov/K-PlanesBSD-3-Clausehttps://github.com/sarafridov/K-PlanesK-Planes reference implementation (Fridovich-Keil et al., 2301.10241).
muskie82/MonoGSLicense notice in repo (research-only) (non-permissive)https://github.com/muskie82/MonoGSGaussian Splatting SLAM official code (Matsuki et al., 2312.06741).
Anttwo/SuGaRCustom (research-only, inherits from upstream 3DGS) (non-permissive)https://github.com/Anttwo/SuGaRSuGaR reference implementation (Guédon & Lepetit, 2311.12775).
3DTopia/LGMMIThttps://github.com/3DTopia/LGMLGM reference implementation (Tang et al., 2402.05054).

Internal synthetic content (Phases 4–5)

The following content categories will be authored from scratch by the Tesserae maintainers (Claude-drafted, human-reviewed) and are not mirrored from any external source. They are released under the same license as the rest of the Tesserae repository (see top-level LICENSE).

  • Daily digests (data/research/daily/*/digest.md, 6 files) — fabricated narrative roundups; cite real corpus papers/repos but the prose is original.
  • Weekly syntheses (data/research/weekly/*/synthesis.md, 2 files) — original essays synthesizing the digests.
  • Open questions (data/research/questions/*.md, 3 files) — original research-gap framings.
  • Agent session transcripts (.agent-sessions/*/transcript.jsonl) — fabricated demonstrations of MCP query workflows. Tool names are real (verified against tesserae/mcp_server.py); the conversation is scripted.
  • Corpus README (README.md) — original framing.
  • Paper bodies (data/research/papers/<slug>/paper.md, to be added in Phase 2) — original 200–400 word summaries of each paper's claims, NOT paragraph quotes from the paper body. No copyrighted text from the paper PDFs is reproduced.

What's intentionally excluded

  • Paper PDFs and full paper bodies (only abstracts, which are CC0 on arXiv).
  • Repository source code (only READMEs in Phase 3, license-permitting).
  • Author photographs, dataset images, or any media files.

Auditing this corpus

Every paper-abstract file carries license: CC0 (arXiv abstract) in its frontmatter. To verify:

grep -lE '^license: CC0' examples/demo-corpus/data/research/papers/*/abstract.md | wc -l   # expect 50