Dynamic Scene Reconstruction

Overview

Dynamic scene reconstruction estimates how a scene’s geometry, appearance, and motion change over time, enabling novel-view rendering, mapping, and simulation. Methods use neural radiance fields, 3D and 4D Gaussian splatting, meshes, or point-based models, guided by cues such as depth, optical flow, camera motion, object identity, and physical constraints. Work spans monocular and multi-view video, from deformable objects and human interactions to driving scenes, and increasingly uses feed-forward models alongside slower per-scene optimization. A central challenge is that realistic-looking renderings do not always imply accurate geometry or motion; methods must balance fidelity, physical plausibility, speed, and robustness to sparse views, occlusion, and long sequences.

Latest papers

CardsList

290 papers35 papers in the last four weeks, up 30% on the four weeks before. 0.2% of all new papers.

  1. Volley3D: Unified 3D Full-Sequence Reconstruction from Monocular Broadcasts

    Oct 28, 2026Noâm Boussouf, Adrien Maglo, Mohamed Chaouch +1Monocular 3D ReconstructionSports Video Analysis

  2. DimFlow: Bidirectional Grid-Expert Learning for Dynamic Gaussian Reconstruction

    Oct 26, 2026Gabriel Adineera, Jinoh KimDynamic Scene Reconstruction4D Reconstruction

  3. SceneAgent: An Agentic Pipeline from 3D and 4D Captures to Simulation Environments

    Oct 26, 2026Luke Hollis, Tianxing Fan, Heng YangRobotics SimulationPhysics-Aware 3D Scene Reconstruction

  4. Stream4D: Streaming 4D Reconstruction with Training-free Motion Decoupling via Causal KV-Cache Attention

    Oct 22, 2026Wei Zhang, Ying Feng, Mengtong Wu +34D ReconstructionDynamic Scene Reconstruction

  5. PhyMo: Learning Physical Dynamics with Accurate and Continuous Motion from Multi-View Videos

    Oct 21, 2026Shangjia Liu, Jinxi Li, Siyuan Zhou +2Dynamic Scene ReconstructionMotion Representation Learning

  6. RayCo4D: Ray-Conditioned Continuous Motion Model for Monocular 4D Dynamic Reconstruction

    Oct 20, 2026Yuanxiang Ni, Xianliang Huang, Ruihan Hou +2Dynamic Scene Reconstruction4D Reconstruction

  7. PointForward V2: Point-Aligned Interaction for Feedforward Driving Reconstruction

    Oct 20, 2026Xianqi Wang, Cheng Chi, Yuechuan Pu +6Dynamic Scene ReconstructionFeed-Forward 3D Reconstruction

  8. HiQGS: Hierarchical Spatiotemporal Querying for Feed-Forward Gaussian Reconstruction

    Oct 20, 2026Qiaowei Miao, Qifeng Cheng, Yijing Guo +33D ReconstructionFeed-Forward 3D Reconstruction

  9. Causal Spatiotemporal State Evolution for Monocular 4D Reconstruction

    Oct 20, 2026Qiaowei Miao, Yijing Guo, Lipei Zhang +44D ReconstructionDynamic Scene Reconstruction

  10. Drive2Gauss: FeedForward 4D Gaussian Reconstruction from Multimodal Generative Driving Videos

    Oct 19, 2026Tong Zhao, Zhiyuan Han, Lin Chen +10Multimodal Video GenerationDynamic Scene Reconstruction

  11. SwitchSplat: Learning Discrete Object States from Casually Captured Scenes

    Oct 17, 2026Yizheng Xie, Yalda Foroutan, George Shramko +33D Scene Representation3D Gaussian Splatting

  12. FLoTS-SLAM: Optical Flow-Derived Uncertainty for Monocular Dynamic SLAM with Two-Stage Optimization

    Oct 16, 2026Haorui Du, Lipu ZhouDynamic SLAMVisual SLAM

  13. Direct Conditional Parameterization for N-Dimensional Splatting

    Oct 16, 2026Zhongpai Gao, Benjamin Planche, Van Nguyen Nguyen +5Gaussian Splatting3D Gaussian Splatting

  14. Motion- and Gravity-Aware Feedforward 3D Reconstruction

    Oct 15, 2026Shiyao Qian, Yuan Ren, Dongfeng BaiMulti-View 3D ReconstructionFeed-Forward 3D Reconstruction

  15. Dusting the Phantom: Gaussian Allocation for Fading Dynamic Content

    Oct 15, 2026Minhyeok Roh, Minseo Lee, Jun Young Jeong +4Dynamic Scene Reconstruction3D Gaussian Splatting

  16. PUGS: Physics-Guided Uncertainty Modeling for Underwater Dynamic 3D Gaussian Splatting

    Oct 13, 2026Tingjun Li, Yuxi Wang, Guoqiang Zhong +1UQ for 3D Reconstruction3D Reconstruction

  17. Gaussian Splatting for Real-Time Scene Reconstruction: Methods, Systems, and Trade-offs

    Oct 13, 2026Ashim Dahal, Rabab Abdelfattah, Nick Rahimi3D Gaussian Splatting3D Reconstruction

  18. Physical SLAM: Physics-aware Simultaneous Localisation and Mapping

    Oct 12, 2026Guangming Wang, Zhishuo Liu, Haibing Wu +4Dynamic Scene Reconstruction3DGS SLAM

  19. CineRecon: Benchmarking Frontier Models for Agentic Cinematic Reconstruction

    Oct 12, 2026Jialei Wang, Zehan Wang, XiaoYang Wu +63D Reconstruction BenchmarksDynamic Scene Reconstruction

  20. PURE: Refining Feed-forward 3D Reconstruction with Unlabeled Post-training

    Oct 10, 2026Yaolong Zhu, Peng Li, Jiahao Lu +83D ReconstructionFeed-Forward 3D Reconstruction

  21. OuroWorld: Bringing Any 3D World Alive as Diverse, Endlessly Looping 3D Cinemagraphs

    Oct 8, 2026You-Zhe Xie, Ting-Wei Chou, Yu-Hsuan Li +33D-Aware Video GenerationDynamic Scene Reconstruction

  22. GenIA: Generative Reconstruction with Test-Time Input Alignment

    Oct 8, 2026Stefano Esposito, Naama Pearl, Polina Karpikova +53D ReconstructionObject-Centric 3D Reconstruction

  23. DynStream: Online Streaming 4D Gaussian Reconstruction of Dynamic Worlds from Unposed Video

    Oct 7, 2026Dingwei Xian, Xiaoyu Zhou, Yajiao Xiong +24D ReconstructionDynamic Scene Reconstruction

  24. Mobile-4DGS: Unified Static-Dynamic Real-time Mobile Gaussian Splatting

    Oct 4, 2026Xiaobiao Du, Zhen Fang, Tianqing Zhu +23DGS Compression3D Gaussian Splatting

  25. Sparse-View 4D Gaussian Splatting via Spatiotemporal Priors and Generative Assistance

    Oct 3, 2026Shengqi Wang, Zhengxian Yang, Kaiwen Tian +6Sparse-View 4D ReconstructionDynamic Scene Reconstruction

  26. 4DCodeBench: Benchmarking Agents on Inverse Graphics of Dynamic Scenes

    Oct 2, 2026Ruihong Shen, Žiga Kovačič, Peter Kulits +6Dynamic Scene ReconstructionAI Agent Benchmarks