https://github.com/nfyfamr/SafeguardGS
공식 코드SafeguardGS: 3D Gaussian Primitive Pruning While Avoiding Catastrophic Scene Destruction
Papers with Code 아카이브
3DGS
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/nickwzk/streamsplat
공식 코드StreamSplat: Towards Online Dynamic 3D Reconstruction from Uncalibrated Video Streams
https://github.com/nnanhuang/s3gaussian
공식 코드$\textit{S}^3$Gaussian: Self-Supervised Street Gaussians for Autonomous Driving
https://github.com/nullptr81/3dgs-accel
공식 코드Taming 3DGS: High-Quality Radiance Fields with Limited Resources
https://github.com/nus-vv-streams/lapis-gs
공식 코드LapisGS: Layered Progressive 3D Gaussian Splatting for Adaptive Streaming
https://github.com/nv-tlabs/3dgrut
공식 코드3DGUT: Enabling Distorted Cameras and Secondary Rays in Gaussian Splatting
https://github.com/nyu-systems/grendel-gs
공식 코드https://github.com/onethousand1000/animportrait3d
공식 코드Text-based Animatable 3D Avatars with Morphable Model Alignment
https://github.com/openxrlab/xrdslam
공식 코드XRDSLAM: A Flexible and Modular Framework for Deep Learning based SLAM
https://github.com/pcl3dv/mgstream
공식 코드MGStream: Motion-aware 3D Gaussian for Streamable Dynamic Scene Reconstruction
https://github.com/peizhiyan/flame-head-tracker
공식 코드https://github.com/peoplelu/dn-4dgs
공식 코드DN-4DGS: Denoised Deformable Network with Temporal-Spatial Aggregation for Dynamic Scene Rendering
https://github.com/poloclub/3D-Gaussian-Splat-Attack
공식 코드https://github.com/prosperolo/gst
공식 코드GST: Precise 3D Human Body from a Single Image with Gaussian Splatting Transformers
https://github.com/prstrive/scgaussian
공식 코드Structure Consistent Gaussian Splatting with Matching Prior for Few-shot Novel View Synthesis
https://github.com/qi-yangsjtu/hybridgs
공식 코드https://github.com/qqqqqqy0227/awesome-3dgs
공식 코드3D Gaussian Splatting: Survey, Technologies, Challenges, and Opportunities
https://github.com/raja-kumar/depth-aware-3dgs
공식 코드Few-shot Novel View Synthesis using Depth Aware 3D Gaussian Splatting
https://github.com/realcrane/student-splating-scooping
공식 코드https://github.com/renaissanceee/mipmap-gs
공식 코드Mipmap-GS: Let Gaussians Deform with Scale-specific Mipmap for Anti-aliasing Rendering
https://github.com/renhaofan/k-buffers
공식 코드K-Buffers: A Plug-in Method for Enhancing Neural Fields with Multiple Buffers
https://github.com/ripl/splart
공식 코드SplArt: Articulation Estimation and Part-Level Reconstruction with 3D Gaussian Splatting
https://github.com/ruyi-zha/r2_gaussian
공식 코드R$^2$-Gaussian: Rectifying Radiative Gaussian Splatting for Tomographic Reconstruction
https://github.com/ry-paper/keyss
공식 코드All That Glitters Is Not Gold: Key-Secured 3D Secrets within 3D Gaussian Splatting
https://github.com/sailor-z/se-gs
공식 코드Self-Ensembling Gaussian Splatting for Few-Shot Novel View Synthesis
https://github.com/salmanali96/trimming-the-fat
공식 코드Trimming the Fat: Efficient Compression of 3D Gaussian Splats through Pruning
https://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/shivangi-aneja/GaussianSpeech
공식 코드https://github.com/shreyesss/hdrsplat
공식 코드HDRSplat: Gaussian Splatting for High Dynamic Range 3D Scene Reconstruction from Raw Images
https://github.com/sim-2-real/wideband3dgs
공식 코드Wideband RF Radiance Field Modeling Using Frequency-embedded 3D Gaussian Splatting
https://github.com/sntubix/denser
공식 코드DENSER: 3D Gaussians Splatting for Scene Reconstruction of Dynamic Urban Environments
https://github.com/spectacularai/3dgs-deblur
공식 코드Gaussian Splatting on the Move: Blur and Rolling Shutter Compensation for Natural Camera Motion
https://github.com/srameo/le3d
공식 코드Lighting Every Darkness with 3DGS: Fast Training and Real-Time Rendering for HDR View Synthesis
https://github.com/sunshinewyc/blockgaussian
공식 코드https://github.com/symmru/EyeNavGS_Software
공식 코드EyeNavGS: A 6-DoF Navigation Dataset and Record-n-Replay Software for Real-World 3DGS Scenes in VR
https://github.com/syxieee/supergs
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.