https://github.com/google-research/google-research/tree/master/regnerf
공식 코드RegNeRF: Regularizing Neural Radiance Fields for View Synthesis from Sparse Inputs
Papers with Code 아카이브
Novel View Synthesis
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 2
- 평가표
- 24
- 보존된 평가 기록
- 103
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.
<span style="color:grey; opacity: 0.6">( Image credit: Multi-view to Novel view: Synthesizing novel views with Self-Learned Confidence )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/google-research/jax3d
공식 코드https://github.com/google-research/multinerf
공식 코드NeRF in the Dark: High Dynamic Range View Synthesis from Noisy Raw Images
https://github.com/google-research/sparf
공식 코드https://github.com/google/stereo-magnification
공식 코드Stereo Magnification: Learning View Synthesis using Multiplane Images
https://github.com/graphdeco-inria/gaussian-splatting
공식 코드3D Gaussian Splatting for Real-Time Radiance Field Rendering
https://github.com/greatdrake/reparameterized-volume-sampling
공식 코드Differentiable Rendering with Reparameterized Volume Sampling
https://github.com/guduxiaolang/gir
공식 코드GIR: 3D Gaussian Inverse Rendering for Relightable Scene Factorization
https://github.com/guillaumerochette/humanviewsynthesis
공식 코드Human Pose Manipulation and Novel View Synthesis using Differentiable Rendering
https://github.com/haeyun-choi/DeepDeblurRF
공식 코드https://github.com/haganelego/manifoldnerf_bmvc2023
공식 코드ManifoldNeRF: View-dependent Image Feature Supervision for Few-shot Neural Radiance Fields
https://github.com/haksorus/gsplatloc
공식 코드https://github.com/hannahhaensen/dynamon
공식 코드DynaMoN: Motion-Aware Fast and Robust Camera Localization for Dynamic Neural Radiance Fields
https://github.com/hannahhaensen/nerftrinsic_four
공식 코드https://github.com/haoyizhu/xnerf
공식 코드X-NeRF: Explicit Neural Radiance Field for Multi-Scene 360$^{\circ} $ Insufficient RGB-D Views
https://github.com/hbb1/2d-gaussian-splatting
공식 코드2D Gaussian Splatting for Geometrically Accurate Radiance Fields
https://github.com/hcp16/active_nerf
공식 코드ActiveNeRF: Learning Accurate 3D Geometry by Active Pattern Projection
https://github.com/heheyas/v3d
공식 코드https://github.com/hexagonprime/pix2nerf
공식 코드Pix2NeRF: Unsupervised Conditional $π$-GAN for Single Image to Neural Radiance Fields Translation
https://github.com/hhsinping/stylescene
공식 코드https://github.com/hkclynn/revorf
공식 코드Learning with Unreliability: Fast Few-shot Voxel Radiance Fields with Relative Geometric Consistency
https://github.com/hku-medai/lig
공식 코드https://github.com/hossein-momeni/diffvox
공식 코드Differentiable Voxel-based X-ray Rendering Improves Sparse-View 3D CBCT Reconstruction
https://github.com/humansplat/humansplat.github.io
공식 코드HumanSplat: Generalizable Single-Image Human Gaussian Splatting with Structure Priors
https://github.com/huntorochi/HoGS
공식 코드HoGS: Unified Near and Far Object Reconstruction via Homogeneous Gaussian Splatting
https://github.com/hwjiang1510/LEAP
공식 코드https://github.com/iSach/SoccerNeRFs
공식 코드https://github.com/icvteam/ipsm
공식 코드https://github.com/ingra14m/deformable-3d-gaussians
공식 코드Deformable 3D Gaussians for High-Fidelity Monocular Dynamic Scene Reconstruction
https://github.com/intel-isl/FreeViewSynthesis
공식 코드https://github.com/intellabs/cgvqm
공식 코드https://github.com/intellabs/clnerf
공식 코드https://github.com/isee-laboratory/rogsplat
공식 코드RoGSplat: Learning Robust Generalizable Human Gaussian Splatting from Sparse Multi-View Images
https://github.com/isl-org/objects-with-lighting
공식 코드https://github.com/ispc-lab/lidar4d
공식 코드LiDAR4D: Dynamic Neural Fields for Novel Space-time View LiDAR Synthesis
https://github.com/ivrl/volrecon
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.