Paper · ≈ 1 min read
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
Outgoing relations
- implemented_in → About bmild/nerf (Repository)
- part_of → 3D/4D Vision and Reconstruction (ResearchField)
- uses → Volumetric Rendering (MethodologicalConcept)
- uses_dataset → LLFF (Dataset)
- uses_metric → LPIPS (Metric)
- uses_metric → PSNR (Metric)
- uses_metric → SSIM (Metric)
Incoming relations
- mentioned_in → About bmild/nerf (Repository)
Connected node types
- Metric: 3
- Repository: 2
- Dataset: 1
- MethodologicalConcept: 1
- ResearchField: 1
Mentions in the corpus
- part_of Evidence: We present a method that achieves state-of-the-art results for synthesi…
- mentioned_in Claim: We present a method that achieves state-of-the-art results for synthesizing novel views of comp…
- part_of Evidence: We describe how to effectively optimize neural radiance fields to rende…
- part_of Evidence: introduce Neural Radiance Fields (NeRF), a scene representation that en…
- mentioned_in Claim: introduce Neural Radiance Fields (NeRF), a scene representation that encodes a continuous volum…
- part_of Evidence: Quantitative results on synthetic and real datasets outperform contempo…
- mentioned_in About bmild/nerf
- summarizes Project Pulse
- summarizes Field Overview — 3D/4D Vision and Reconstruction
Cross-references in raw data
Source provenance
examples/demo-corpus/data/research/papers/arxiv-2003-08934/abstract.md