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awesome-dynamic-scene-reconstruction
A curated list of awesome neural scene reconstruction datasets and papers, inspired by awesome-computer-vision.
https://github.com/DynaVis/awesome-dynamic-scene-reconstruction
Last synced: 3 days ago
JSON representation
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Papers
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General Scenes
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- DynIBaR Neural Dynamic Image-Based Rendering
- DynamicStereo: Consistent Dynamic Depth from Stereo Videos - stereo.github.io/) <br> [code](https://github.com/facebookresearch/dynamic_stereo)|
- Temporal Interpolation Is All You Need for Dynamic Neural Radiance Fields
- HexPlane: A Fast Representation for Dynamic Scenes
- NeRF-DS: Neural Radiance Fields for Dynamic Specular Objects - ds/) <br> [code](https://github.com/JokerYan/NeRF-DS) <br> [data](https://github.com/JokerYan/NeRF-DS/releases/tag/v0.1-pre-release) |
- RoDynRF:Robust Dynamic Radiance Fields - dynrf.github.io/?ref=dataphoenix.info)|
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- DyLiN: Making Light Field Networks Dynamic
- Neural 3D Video Synthesis from Multi-view Video - 3d-video.github.io/) <br> [data](https://github.com/facebookresearch/Neural_3D_Video) |
- OcclusionFusion: Occlusion-aware Motion Estimation for Real-time Dynamic 3D Reconstruction - lin.github.io/OcclusionFusion/) <br> [code](https://github.com/wenbin-lin/OcclusionFusion/) |
- DeepDeform: Learning Non-rigid RGB-D Reconstruction with Semi-supervised Data
- Hybrid Modeling of Non-Rigid Scenes From RGBD Cameras
- General Dynamic Scene Reconstruction from Multiple View Video
- Monocular 3D Reconstruction of Locally Textured Surfaces - dsr-index-php/)|
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- Multi-view Occlusion Reasoning for Probabilistic Silhouette-Based Dynamic Scene Reconstruction - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
- 3D Reconstruction of Dynamic Scenes with Multiple Handheld Cameras - |
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Human-centric
- HumanRF: High-Fidelity Neural Radiance Fields for Humans in Motion - hq.com/)|
- BEDLAM: A Synthetic Dataset of Bodies Exhibiting Detailed Lifelike Animated Motion
- Learning Neural Volumetric Representations of Dynamic Humans in Minutes - nvr/) <br> [data](https://github.com/zju3dv/instant-nvr/blob/master/docs/install.md#set-up-datasets)|
- Tensor4D : Efficient Neural 4D Decomposition for High-fidelity Dynamic Reconstruction and Rendering - my.sharepoint.com/:f:/g/personal/shaorz20_mails_tsinghua_edu_cn/EsNxn0pJ19lFrRMKAS1YDx0Bv_V9LAdub9jnYvT40QZEDA?e=ChbsFX)|
- Representing Volumetric Videos as Dynamic MLP Maps
- Function4D: Real-time Human Volumetric Capture from Very Sparse Consumer RGBD Sensors - Dataset)|
- SIZER: A Dataset and Model for Parsing 3D Clothing and Learning Size Sensitive 3D Clothing - inf.mpg.de/sizer/) <br> [code](https://github.com/garvita-tiwari/sizer) <br> [data](https://nextcloud.mpi-klsb.mpg.de/index.php/s/nx6wK6BJFZCTF8C/authenticate/showShare) |
- DeepHuman: 3D Human Reconstruction from a Single Image
- 3DPeople: Modeling the Geometry of Dressed Humans - csic.es/) |
- Dynamic FAUST: Registering Human Bodies in Motion - cvpr-2017) <br> [data](https://dfaust.is.tue.mpg.de/)|
- Learning from Synthetic Humans
- Articulated Mesh Animation from Multi-view Silhouettes
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Dataset Repositories
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Human-centric
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