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NeRF
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/vincentfung13/MINE
공식 코드MINE: Towards Continuous Depth MPI with NeRF for Novel View Synthesis
https://github.com/vincentqqu/nerf-nqa
공식 코드https://github.com/vincentqqu/nvs-sqa
공식 코드https://github.com/vineetkumarrakesh/thg
공식 코드https://github.com/vision-sjtu/lightning-nerf
공식 코드Lightning NeRF: Efficient Hybrid Scene Representation for Autonomous Driving
https://github.com/vita-group/aug-nerf
공식 코드https://github.com/vita-group/gnt-move
공식 코드Enhancing NeRF akin to Enhancing LLMs: Generalizable NeRF Transformer with Mixture-of-View-Experts
https://github.com/vita-group/nerf-sos
공식 코드NeRF-SOS: Any-View Self-supervised Object Segmentation on Complex Scenes
https://github.com/vlar-group/dm-nerf
공식 코드DM-NeRF: 3D Scene Geometry Decomposition and Manipulation from 2D Images
https://github.com/vlar-group/nvfi
공식 코드https://github.com/vppyw/Stylized-NeRF-with-AdaIN
공식 코드https://github.com/wagnva/semantic-nerf-for-satellite-data
공식 코드Semantic Neural Radiance Fields for Multi-Date Satellite Data
https://github.com/wangyida/ra-neus
공식 코드https://github.com/wayne1123/code-nerf
공식 코드CodeNeRF: Disentangled Neural Radiance Fields for Object Categories
https://github.com/weihangliu2024/content_aware_nerf
공식 코드https://github.com/weiyithu/nerfingmvs
공식 코드NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo
https://github.com/wengflow/robust-e-nerf
공식 코드Robust e-NeRF: NeRF from Sparse & Noisy Events under Non-Uniform Motion
https://github.com/wentxul/linr
공식 코드Revisiting Implicit Neural Representations in Low-Level Vision
https://github.com/wenwhx/nerfdirector
공식 코드NeRF Director: Revisiting View Selection in Neural Volume Rendering
https://github.com/windingwind/seal-3d
공식 코드Seal-3D: Interactive Pixel-Level Editing for Neural Radiance Fields
https://github.com/wljungbergh/neuroncap
공식 코드NeuroNCAP: Photorealistic Closed-loop Safety Testing for Autonomous Driving
https://github.com/wojtekz4/nerflame
공식 코드NeRFlame: FLAME-based conditioning of NeRF for 3D face rendering
https://github.com/wrk226/garmentanimationnerf
공식 코드https://github.com/wrld/uc-nerf
공식 코드UC-NeRF: Uncertainty-aware Conditional Neural Radiance Fields from Endoscopic Sparse Views
https://github.com/wu-cvgl/casualhdrsplat
공식 코드CasualHDRSplat: Robust High Dynamic Range 3D Gaussian Splatting from Casually Captured Videos
https://github.com/wu-cvgl/inceventgs
공식 코드IncEventGS: Pose-Free Gaussian Splatting from a Single Event Camera
https://github.com/wu-cvgl/mba-slam
공식 코드MBA-SLAM: Motion Blur Aware Dense Visual SLAM with Radiance Fields Representation
https://github.com/wu-cvgl/scinerf
공식 코드SCINeRF: Neural Radiance Fields from a Snapshot Compressive Image
https://github.com/wuuu3511/sparse2dgs
공식 코드Sparse2DGS: Geometry-Prioritized Gaussian Splatting for Surface Reconstruction from Sparse Views
https://github.com/wyhuai/NeRFocus
공식 코드https://github.com/xiaobiaodu/MVGS
공식 코드MVGS: Multi-view-regulated Gaussian Splatting for Novel View Synthesis
https://github.com/xiaohao-xu/slam-under-perturbation
공식 코드https://github.com/xiaohao-xu/unified-pretrain-ad
공식 코드https://github.com/xingy038/conrf
공식 코드ConRF: Zero-shot Stylization of 3D Scenes with Conditioned Radiation Fields
https://github.com/xingy038/ctnerf
공식 코드CTNeRF: Cross-Time Transformer for Dynamic Neural Radiance Field from Monocular Video
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.