https://github.com/Xrvitd/SuperGaussians
공식 코드SuperGaussians: Enhancing Gaussian Splatting Using Primitives with Spatially Varying Colors
Papers with Code 아카이브
Novel View Synthesis
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 2
- 평가표
- 24
- 보존된 평가 기록
- 103
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/XuyangSHEN/Pairwise-GAN
공식 코드Pairwise-GAN: Pose-based View Synthesis through Pair-Wise Training
https://github.com/Yeyuqqwx/HybridGS
공식 코드HybridGS: Decoupling Transients and Statics with 2D and 3D Gaussian Splatting
https://github.com/Yizhe-Liu/SplatPosePlus
공식 코드SplatPose+: Real-time Image-Based Pose-Agnostic 3D Anomaly Detection
https://github.com/YorkUCVIL/Photoconsistent-NVS
공식 코드Long-Term Photometric Consistent Novel View Synthesis with Diffusion Models
https://github.com/YueWuHKUST/ICCV2021-Embedding-Novel-Views-in-a-Single-JPEG-Image
공식 코드https://github.com/activevisionlab/dfnet
공식 코드DFNet: Enhance Absolute Pose Regression with Direct Feature Matching
https://github.com/ai4ce/EUVS-Benchmark
공식 코드https://github.com/aibluefisher/dogs
공식 코드https://github.com/aibluefisher/dreg-nerf
공식 코드https://github.com/aiolus-x/norm-inr
공식 코드Towards the Spectral bias Alleviation by Normalizations in Coordinate Networks
https://github.com/aipixel/gps-gaussian
공식 코드https://github.com/ais-bonn/neural_mvs
공식 코드NeuralMVS: Bridging Multi-View Stereo and Novel View Synthesis
https://github.com/ajayjain/DietNeRF
공식 코드Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis
https://github.com/ajhamdi/ges-splatting
공식 코드GES: Generalized Exponential Splatting for Efficient Radiance Field Rendering
https://github.com/ajhamdi/sparf_pytorch
공식 코드SPARF: Large-Scale Learning of 3D Sparse Radiance Fields from Few Input Images
https://github.com/alexberian/crossmodalitydiffusion
공식 코드CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation
https://github.com/alexj94/future_urban_scene_generation
공식 코드https://github.com/alexkeroro86/samplenerfro
공식 코드https://github.com/algohunt/streamrf
공식 코드https://github.com/alvaro-budria/InstantGeoAvatar
공식 코드https://github.com/amadeusstq/topology-gs
공식 코드https://github.com/andypinxinliu/HumanFaceProject/tree/main/assets/GaussianStyle
공식 코드https://github.com/angchen-dev/hemisparsegs
공식 코드https://github.com/apchenstu/TensoRF
공식 코드https://github.com/apple/ml-hugs
공식 코드https://github.com/arclab-mit/space-nvs
공식 코드DreamSat: Towards a General 3D Model for Novel View Synthesis of Space Objects
https://github.com/astra-vision/SceneRF
공식 코드SceneRF: Self-Supervised Monocular 3D Scene Reconstruction with Radiance Fields
https://github.com/autonomousvision/graf
공식 코드GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis
https://github.com/autonomousvision/gta
공식 코드GTA: A Geometry-Aware Attention Mechanism for Multi-View Transformers
https://github.com/autonomousvision/kitti360labeltool
공식 코드KITTI-360: A Novel Dataset and Benchmarks for Urban Scene Understanding in 2D and 3D
https://github.com/autonomousvision/kitti360scripts
공식 코드KITTI-360: A Novel Dataset and Benchmarks for Urban Scene Understanding in 2D and 3D
https://github.com/autonomousvision/neat
공식 코드NEAT: Neural Attention Fields for End-to-End Autonomous Driving
https://github.com/autonomousvision/unisurf
공식 코드UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for Multi-View Reconstruction
https://github.com/autonomousvision/voxgraf
공식 코드VoxGRAF: Fast 3D-Aware Image Synthesis with Sparse Voxel Grids
https://github.com/avinashpaliwal/ReShader
공식 코드ReShader: View-Dependent Highlights for Single Image View-Synthesis
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.