https://github.com/facebookresearch/pytorch3d/tree/master/projects/nerf
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
Papers with Code 아카이브
Neural Rendering
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Given a representation of a 3D scene of some kind (point cloud, mesh, voxels, etc.), the task is to create an algorithm that can produce photorealistic renderings of this scene from an arbitrary viewpoint. Sometimes, the task is accompanied by image/scene appearance manipulation.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/fbxiang/NeuTex
NeuTex: Neural Texture Mapping for Volumetric Neural Rendering
https://github.com/filby89/spectre
https://github.com/flynn-chen/faceforensics_benchmark
Deferred Neural Rendering: Image Synthesis using Neural Textures
https://github.com/georghess/neurad
SplatAD: Real-Time Lidar and Camera Rendering with 3D Gaussian Splatting for Autonomous Driving
https://github.com/glouppe/info8010-deep-learning
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
https://github.com/google-deepmind/spriteworld
Spatial Broadcast Decoder: A Simple Architecture for Learning Disentangled Representations in VAEs
https://github.com/googleinterns/ibrnet
https://github.com/huangkun101230/360mtlgeometricestimation
GaussianShader: 3D Gaussian Splatting with Shading Functions for Reflective Surfaces
https://github.com/husheng12345/Unofficial-NeRF-Supervised-Deep-Stereo
https://github.com/idiap/geonerf
https://github.com/ingra14m/Lightweight-Deformable-GS
Deformable 3D Gaussians for High-Fidelity Monocular Dynamic Scene Reconstruction
https://github.com/jamesperlman/nerfrendercore
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
https://github.com/jiepengwang/NeuRIS
NeuRIS: Neural Reconstruction of Indoor Scenes Using Normal Priors
https://github.com/jingma-git/NeRF_Pytorch
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
https://github.com/kair-bair/nerfacc
Instant Neural Graphics Primitives with a Multiresolution Hash Encoding
https://github.com/kakaobrain/NeRF-Factory
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
https://github.com/keras-team/keras-io/blob/master/examples/vision/nerf.py
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
https://github.com/kklemon/gon-pytorch
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
https://github.com/km3888/zeroforge
Neural Voxel Renderer: Learning an Accurate and Controllable Rendering Tool
https://github.com/komeiharada/learn_DL_together
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
https://github.com/krrish94/nerf-pytorch
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
https://github.com/kwea123/nerf_pl
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
https://github.com/kwea123/ngp_pl
Instant Neural Graphics Primitives with a Multiresolution Hash Encoding
https://github.com/laura-a-n-n/tf-nlr
https://github.com/leminhbinh0209/add
Deferred Neural Rendering: Image Synthesis using Neural Textures
https://github.com/letianhuang/op43dgs
On the Error Analysis of 3D Gaussian Splatting and an Optimal Projection Strategy
https://github.com/lizuoyue/sat2scene
Sat2Scene: 3D Urban Scene Generation from Satellite Images with Diffusion
https://github.com/lucidrains/pi-GAN-pytorch
pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesis
https://github.com/lukaszbinden/spatial-broadcast-decoder
Spatial Broadcast Decoder: A Simple Architecture for Learning Disentangled Representations in VAEs
https://github.com/lvsn/ZeroComp
https://github.com/m-schuetz/compute_rasterizer
https://github.com/matsuren/nerf_jax_flax_practice
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
https://github.com/megvii-research/conr
https://github.com/megvii-research/ijcai2023-conr
https://github.com/mmlofficial/MALIVAR-ML-Engineer-Test
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.