https://github.com/520jz/spikegs
공식 코드SpikeGS: Learning 3D Gaussian Fields from Continuous Spike Stream
Papers with Code 아카이브
Novel View Synthesis
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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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/AaltoVision/warped-skipconnection-nvs
공식 코드https://github.com/ActiveVisionLab/direct-posenet
공식 코드Direct-PoseNet: Absolute Pose Regression with Photometric Consistency
https://github.com/ActiveVisionLab/nerfmm
공식 코드NeRF--: Neural Radiance Fields Without Known Camera Parameters
https://github.com/AlvinZhuyx/camera_pose_representation
공식 코드https://github.com/AronKovacs/g-style
공식 코드https://github.com/Aswhalefall/VISTA
공식 코드Visibility-Uncertainty-guided 3D Gaussian Inpainting via Scene Conceptional Learning
https://github.com/BaowenZ/RaDe-GS
공식 코드https://github.com/Brummi/BehindTheScenes
공식 코드Behind the Scenes: Density Fields for Single View Reconstruction
https://github.com/CVMI-Lab/HybridNeuralRendering
공식 코드Hybrid Neural Rendering for Large-Scale Scenes with Motion Blur
https://github.com/Caoang327/HexPlane
공식 코드https://github.com/ChenYutongTHU/SplatFormer
공식 코드SplatFormer: Point Transformer for Robust 3D Gaussian Splatting
https://github.com/CompVis/geometry-free-view-synthesis
공식 코드https://github.com/DNA-Rendering/DNA-Rendering
공식 코드DNA-Rendering: A Diverse Neural Actor Repository for High-Fidelity Human-centric Rendering
https://github.com/DekuLiuTesla/CityGaussian
공식 코드CityGaussian: Real-time High-quality Large-Scale Scene Rendering with Gaussians
https://github.com/Factral/UnMix-NeRF
공식 코드https://github.com/ForMyCat/SparseGS
공식 코드SparseGS: Real-Time 360° Sparse View Synthesis using Gaussian Splatting
https://github.com/GopiRajuMatta/BeSplat
공식 코드BeSplat: Gaussian Splatting from a Single Blurry Image and Event Stream
https://github.com/HITSZ-NRSL/MSI-NeRF
공식 코드https://github.com/Haian-Jin/TensoIR
공식 코드https://github.com/IntelLabs/baa-ngp
공식 코드BAA-NGP: Bundle-Adjusting Accelerated Neural Graphics Primitives
https://github.com/Inter3D-ui/Inter3D
공식 코드Inter3D: A Benchmark and Strong Baseline for Human-Interactive 3D Object Reconstruction
https://github.com/JOP-Lee/READ-Large-Scale-Neural-Scene-Rendering-for-Autonomous-Driving
공식 코드READ: Large-Scale Neural Scene Rendering for Autonomous Driving
https://github.com/JanaldoChen/Anim-NeRF
공식 코드https://github.com/JiatongXia/Pseudo-Labeling
공식 코드https://github.com/Jixuan-Fan/Momentum-GS
공식 코드Momentum-GS: Momentum Gaussian Self-Distillation for High-Quality Large Scene Reconstruction
https://github.com/JonathonLuiten/Dynamic3DGaussians
공식 코드Dynamic 3D Gaussians: Tracking by Persistent Dynamic View Synthesis
https://github.com/KU-CVLAB/3DGAN-Inversion
공식 코드https://github.com/KU-CVLAB/CoPoNeRF
공식 코드Unifying Correspondence, Pose and NeRF for Pose-Free Novel View Synthesis from Stereo Pairs
https://github.com/KU-CVLAB/DaRF
공식 코드DaRF: Boosting Radiance Fields from Sparse Inputs with Monocular Depth Adaptation
https://github.com/KU-CVLAB/RAIN-GS
공식 코드Relaxing Accurate Initialization Constraint for 3D Gaussian Splatting
https://github.com/KU-CVLAB/SE-NeRF
공식 코드https://github.com/KeKsBoTer/c3dgs
공식 코드Compressed 3D Gaussian Splatting for Accelerated Novel View Synthesis
https://github.com/KovenYu/uORF
공식 코드https://github.com/LZleejean/TexIR_code
공식 코드Multi-view Inverse Rendering for Large-scale Real-world Indoor Scenes
https://github.com/Lakonik/SSDNeRF
공식 코드Single-Stage Diffusion NeRF: A Unified Approach to 3D Generation and Reconstruction
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.