SOTAVerified

Novel View Synthesis

Synthesize a target image with an arbitrary target camera pose from given source images and their camera poses.

See Wiki for more introductions.

The Synthesis method include: NeRF, MPI and so on.

( Image credit: Multi-view to Novel view: Synthesizing novel views with Self-Learned Confidence )

Papers

Showing 110 of 1441 papers

TitleStatusHype
Physically Based Neural LiDAR ResimulationCode0
Cameras as Relative Positional Encoding0
MoVieS: Motion-Aware 4D Dynamic View Synthesis in One Second0
LighthouseGS: Indoor Structure-aware 3D Gaussian Splatting for Panorama-Style Mobile Captures0
Reflections Unlock: Geometry-Aware Reflection Disentanglement in 3D Gaussian Splatting for Photorealistic Scenes Rendering0
Outdoor Monocular SLAM with Global Scale-Consistent 3D Gaussian Pointmaps0
Refine Any Object in Any SceneCode1
VoteSplat: Hough Voting Gaussian Splatting for 3D Scene Understanding0
UnMix-NeRF: Spectral Unmixing Meets Neural Radiance FieldsCode1
DBMovi-GS: Dynamic View Synthesis from Blurry Monocular Video via Sparse-Controlled Gaussian Splatting0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1R3F-OracleAverage PSNR (dB)29.34Unverified
2Zip-NeRFAverage PSNR (dB)26.11Unverified
3R3FAverage PSNR (dB)24.95Unverified
4Ray Deformation NetworkAverage PSNR (dB)23.13Unverified
5Rose-NeRFAverage PSNR (dB)22.86Unverified
6NeuSAverage PSNR (dB)19.62Unverified
7SplatfactoAverage PSNR (dB)19.53Unverified
8TNSRAverage PSNR (dB)18.64Unverified