https://github.com/ruyi-zha/r2_gaussian
공식 코드R$^2$-Gaussian: Rectifying Radiative Gaussian Splatting for Tomographic Reconstruction
Papers with Code 아카이브
NeRF
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/rvp-group/Splat-LOAM
공식 코드https://github.com/rzhevcherkasy/bmvc24-gsim
공식 코드Gaussian Splatting in Mirrors: Reflection-Aware Rendering via Virtual Camera Optimization
https://github.com/s3anwu/pbrnerf
공식 코드PBR-NeRF: Inverse Rendering with Physics-Based Neural Fields
https://github.com/samuel-cerezo/SLAM-Render
공식 코드SLAM&Render: A Benchmark for the Intersection Between Neural Rendering, Gaussian Splatting and SLAM
https://github.com/sandergielisse/mwt
공식 코드End-to-End Implicit Neural Representations for Classification
https://github.com/sararoma95/Re-ReND
공식 코드https://github.com/sarroccoluigi/combinerf
공식 코드https://github.com/saskiarabich/fpoplusplus
공식 코드https://github.com/sbsws88/tfs_nerf
공식 코드TFS-NeRF: Template-Free NeRF for Semantic 3D Reconstruction of Dynamic Scene
https://github.com/schindlerepfl/thermo-nerf
공식 코드https://github.com/scut-bip-lab/ea-3dgs
공식 코드EA-3DGS: Efficient and Adaptive 3D Gaussians with Highly Enhanced Quality for outdoor scenes
https://github.com/seanywang0408/radiancemapping
공식 코드https://github.com/semchan/UPST-NeRF
공식 코드UPST-NeRF: Universal Photorealistic Style Transfer of Neural Radiance Fields for 3D Scene
https://github.com/sen-mao/3di2i-translation
공식 코드https://github.com/seoha-kim/Sync-NeRF
공식 코드Sync-NeRF: Generalizing Dynamic NeRFs to Unsynchronized Videos
https://github.com/sevashasla/usf
공식 코드https://github.com/sfchng/Gaussian-Activated-Radiance-Fields
공식 코드GARF: Gaussian Activated Radiance Fields for High Fidelity Reconstruction and Pose Estimation
https://github.com/shad0wta9/meshavatar
공식 코드MeshAvatar: Learning High-quality Triangular Human Avatars from Multi-view Videos
https://github.com/shawn615/FlipNeRF
공식 코드FlipNeRF: Flipped Reflection Rays for Few-shot Novel View Synthesis
https://github.com/shawn615/MixNeRF
공식 코드MixNeRF: Modeling a Ray with Mixture Density for Novel View Synthesis from Sparse Inputs
https://github.com/sheldonmao/neuspir
공식 코드NeuS-PIR: Learning Relightable Neural Surface using Pre-Integrated Rendering
https://github.com/shiran-yuan/slimmerf
공식 코드https://github.com/showlab/devrf
공식 코드DeVRF: Fast Deformable Voxel Radiance Fields for Dynamic Scenes
https://github.com/showlab/headshot
공식 코드https://github.com/shreyesss/hdrsplat
공식 코드HDRSplat: Gaussian Splatting for High Dynamic Range 3D Scene Reconstruction from Raw Images
https://github.com/shreyvish5678/SR-NeRF-with-Variational-Diffusion-Strategies
공식 코드Advancing Super-Resolution in Neural Radiance Fields via Variational Diffusion Strategies
https://github.com/shreyvish5678/advancing-super-resolution-in-neural-radiance-fields-via-variational-diffusion-strategies
공식 코드Advancing Super-Resolution in Neural Radiance Fields via Variational Diffusion Strategies
https://github.com/silence-tang/artnerf
공식 코드ArtNeRF: A Stylized Neural Field for 3D-Aware Cartoonized Face Synthesis
https://github.com/sjj118/normal-nerf
공식 코드Normal-NeRF: Ambiguity-Robust Normal Estimation for Highly Reflective Scenes
https://github.com/sjojok/vgos
공식 코드VGOS: Voxel Grid Optimization for View Synthesis from Sparse Inputs
https://github.com/sjtuzq/point-radiance
공식 코드Differentiable Point-Based Radiance Fields for Efficient View Synthesis
https://github.com/skhu101/consistentnerf
공식 코드ConsistentNeRF: Enhancing Neural Radiance Fields with 3D Consistency for Sparse View Synthesis
https://github.com/skhu101/gauhuman
공식 코드GauHuman: Articulated Gaussian Splatting from Monocular Human Videos
https://github.com/skhu101/humangif
공식 코드https://github.com/skhu101/sherf
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.