{"id":14669547,"url":"https://github.com/cwchenwang/awesome-4d-generation","last_synced_at":"2025-09-08T23:31:31.104Z","repository":{"id":236564889,"uuid":"790897405","full_name":"cwchenwang/awesome-4d-generation","owner":"cwchenwang","description":"List of papers on 4D 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Resources","Other Lists"],"sub_categories":["Survey and Awesome Repos","TeX Lists"],"readme":"# Awesome 4D Generation\nThis repo collects papers for 4D generation.\n\n## Table of Contents\n- [Camera Control for Video Diffusion](#camera-control-for-video-diffusion)\n- [Multi-view for Video Diffusion](#multi-view-for-video-diffusion)\n- [Distillation from Video Diffusion](#distillation-from-video-diffusion)\n- [Generation by Reconstruction](#generation-by-reconstruction)\n- [4D Editing](#4d-editing)\n- [Physics](#physics)\n\n## Camera Control for Video Diffusion\n\nVD3D: Taming Large Video Diffusion Transformers for 3D Camera Control\n\n[📄 Paper](https://arxiv.org/abs/2407.12781) | [🌐 Project Page](https://snap-research.github.io/vd3d/)\n\nControlling Space and Time with Diffusion Models\n\n[📄 Paper](https://arxiv.org/pdf/2407.07860) | [🌐 Project Page](https://4d-diffusion.github.io/)\n\nCamCo: Camera-Controllable 3D-Consistent Image-to-Video Generation\n\n[📄 Paper](https://arxiv.org/abs/2406.02509) | [🌐 Project Page](https://ir1d.github.io/CamCo/)\n\nCollaborative Video Diffusion: Consistent Multi-video Generation with Camera Control\n\n[📄 Paper](https://arxiv.org/pdf/2405.17414) | [🌐 Project Page](https://collaborativevideodiffusion.github.io/)\n\n## Multi-view for Video Diffusion\n\nSV4D: Dynamic 3D Content Generation with Multi-Frame and Multi-View Consistency, Xie et al., Arxiv 2024\n\n[📄 Paper](https://arxiv.org/pdf/2407.17470) | [🌐 Project Page](https://sv4d.github.io/) | [💻 Code](https://github.com/Stability-AI/generative-models)\n\nL4GM: Large 4D Gaussian Reconstruction Model, Ren et al., Arxiv 2024\n\n[📄 Paper](https://arxiv.org/abs/2406.10324) | [🌐 Project Page](https://research.nvidia.com/labs/toronto-ai/l4gm/)\n\n4Diffusion: Multi-view Video Diffusion Model for 4D Generation, Zhang et al., Arxiv 2024\n\n[📄 Paper](https://arxiv.org/pdf/2405.20674) | [🌐 Project Page](https://aejion.github.io/4diffusion) | [💻 Code](https://github.com/aejion/4Diffusion) \n\nDiffusion4D: Fast Spatial-temporal Consistent 4D Generation via Video Diffusion Models, Liang et al., Arxiv 2024\n\n[📄 Paper](https://arxiv.org/abs/2405.16645) | [🌐 Project Page](https://vita-group.github.io/Diffusion4D/) | [💻 Code](https://github.com/VITA-Group/Diffusion4D) | [🎥 Video](https://www.youtube.com/watch?v=XJT-cMt_xVo)\n\n## Distillation from Video Diffusion\nTrans4D: Realistic Geometry-Aware Transition for Compositional Text-to-4D Synthesis, Zeng et al., Arxiv 2024\n\n[📄 Paper](https://arxiv.org/abs/2410.07155) | [💻 Code](https://github.com/YangLing0818/Trans4D)\n\nCT4D: Consistent Text-to-4D Generation with Animatable Meshes, Ce et al., Arxiv 2024\n\n[📄 Paper](https://arxiv.org/pdf/2408.08342)\n\nStreetscapes: Large-scale Consistent Street View Generation Using Autoregressive Video Diffusion, Deng et al., SIGGRAPH 2024\n\n[📄 Paper](https://arxiv.org/pdf/2407.13759) | [🌐 Project Page](https://boyangdeng.com/streetscapes/) | [🎥 Video](https://www.youtube.com/watch?v=13hLTnrVVKk)\n\n4Dynamic: Text-to-4D Generation with Hybrid Priors, Yuan et al., Arxiv 2024\n\n[📄 Paper](https://arxiv.org/abs/2407.12684)\n\nAnimate3D: Animating Any 3D Model with Multi-view Video Diffusion, Jiang et al., Arxiv 2024\n\n[📄 Paper](https://arxiv.org/pdf/2407.11398) | [🌐 Project Page](https://animate3d.github.io/) \n\nSTAR: Skeleton-aware Text-based 4D Avatar Generation with In-Network Motion Retargeting, Chai et al., Arxiv 2024\n\n[📄 Paper](https://arxiv.org/abs/2406.04629) | [🌐 Project Page](https://star-avatar.github.io/) | [💻 Code](https://github.com/czh-98/STAR)\n\nMotionDreamer: Zero-Shot 3D Mesh Animation from Video Diffusion Models, Uzolas et al., Arxiv 2024\n\n[📄 Paper](https://arxiv.org/pdf/2405.20155) | [💻 Code](https://github.com/lukasuz/MotionDreamer)\n\nPLA4D: Pixel-Level Alignments for Text-to-4D Gaussian Splatting, Miao et al., Arxiv 2024\n\n[📄 Paper](https://arxiv.org/pdf/2405.19957) | [🌐 Project Page](https://github.com/MiaoQiaowei/PLA4D.github.io)\n\nMagicPose4D: Crafting Articulated Models with Appearance and Motion Control, Zhang et al., Arxiv 2024\n\n[📄 Paper](https://arxiv.org/pdf/2405.14017) | [🌐 Project Page](https://boese0601.github.io/magicpose4d/) | [💻 Code](https://github.com/haoz19/MagicPose4D) \n\nSC4D: Sparse-Controlled Video-to-4D Generation and Motion Transfer, Wu et al., Arxiv 2024\n\n[📄 Paper](https://arxiv.org/abs/2404.03736) | [🌐 Project Page](https://sc4d.github.io/) | [💻 Code](https://github.com/JarrentWu1031/SC4D) | [🎥 Video](https://www.youtube.com/watch?v=SkpTEuX4B5c)\n\nTC4D: Trajectory-Conditioned Text-to-4D Generation, Bahmani et al., Arxiv 2024\n\n[📄 Paper](https://arxiv.org/pdf/2403.17920) | [🌐 Project Page](https://sherwinbahmani.github.io/tc4d) | [💻 Code](https://github.com/sherwinbahmani/tc4d)\n\nComp4D: LLM-Guided Compositional 4D Scene Generation, Xu et al., Arxiv 2024\n\n[📄 Paper](https://arxiv.org/abs/2403.16993) | [🌐 Project Page](https://vita-group.github.io/Comp4D/) | [💻 Code](https://github.com/VITA-Group/Comp4D) | [🎥 Video](https://www.youtube.com/watch?v=9q8SV1Xf_Xw)\n\nSTAG4D: Spatial-Temporal Anchored Generative 4D Gaussians, Zetn et al., Arxiv 2024\n\n[📄 Paper](https://arxiv.org/pdf/2403.14939.pdf) | [🌐 Project Page](https://nju-3dv.github.io/projects/STAG4D/) | [💻 Code](https://github.com/zeng-yifei/STAG4D) \n\nGaussianFlow: Splatting Gaussian Dynamics for 4D Content Creation, Gao et al., Arxiv 2024\n\n[📄 Paper](https://arxiv.org/abs/2403.12365) | [🌐 Project Page](https://zerg-overmind.github.io/GaussianFlow.github.io/) | [💻 Code](https://github.com/Zerg-Overmind/GaussianFlow)\n\n4DGen: Grounded 4D Content Generation with Spatial-temporal Consistency, Yin et al., Arxiv 2023\n\n[📄 Paper](https://arxiv.org/pdf/2312.17225) | [🌐 Project Page](https://vita-group.github.io/4DGen/) | [💻 Code](https://github.com/VITA-Group/4DGen) | [🎥 Video](https://www.youtube.com/watch?v=-bXyBKdpQ1o)\n\nDreamGaussian4D: Generative 4D Gaussian Splatting, Ren et al., CVPR 2024\n\n[📄 Paper](https://arxiv.org/pdf/2312.13763) | [🌐 Project Page](https://jiawei-ren.github.io/projects/dreamgaussian4d/)\n\nAlign Your Gaussians: Text-to-4D with Dynamic 3D Gaussians and Composed Diffusion Models, Ling et al., Arxiv 2023\n\n[📄 Paper](https://arxiv.org/pdf/2312.03795) | [🌐 Project Page](https://animatabledreamer.github.io/) | [💻 Code](https://github.com/AnimatableDreamer/AnimatableDreamer)\n\nAnimatableDreamer: Text-Guided Non-rigid 3D Model Generation and Reconstruction with Canonical Score Distillation, Wang et al., Arxiv 2023\n\n[📄 Paper](https://arxiv.org/pdf/2312.03795) | [🌐 Project Page](https://animatabledreamer.github.io/) | [💻 Code](https://github.com/AnimatableDreamer/AnimatableDreamer)\n\n4D-fy: Text-to-4D Generation Using Hybrid Score Distillation Sampling, Bahmani et al., CVPR 2024\n\n[📄 Paper](https://arxiv.org/pdf/2311.17984) | [🌐 Project Page](https://research.nvidia.com/labs/nxp/dream-in-4d/) | [💻 Code](https://github.com/sherwinbahmani/4dfy)\n\nA Unified Approach for Text- and Image-guided 4D Scene Generation, Zheng et al., CVPR 2024\n\n[📄 Paper](https://arxiv.org/pdf/2311.17984) | [🌐 Project Page](https://sherwinbahmani.github.io/4dfy) | [💻 Code](https://github.com/NVlabs/dream-in-4d)\n\nAnimate124: Animating One Image to 4D Dynamic Scene, Zhao et al., Arxiv 2023\n\n[📄 Paper](https://arxiv.org/pdf/2311.14603) | [🌐 Project Page](https://animate124.github.io/) | [💻 Code](https://github.com/HeliosZhao/Animate124)\n\nConsistent4D: Consistent 360° Dynamic Object Generation from Monocular Video, Jiang et al., Arxiv 2024\n\n[📄 Paper](https://arxiv.org/pdf/2311.02848) | [🌐 Project Page](https://consistent4d.github.io/) | [💻 Code](https://github.com/yanqinJiang/Consistent4D)\n\nText-To-4D Dynamic Scene Generation, Singer et al., Arxiv 2023\n\n[📄 Paper](https://arxiv.org/pdf/2301.11280) | [🌐 Project Page](https://make-a-video3d.github.io)\n\n## Generation by Reconstruction\n\n4Real: Towards Photorealistic 4D Scene Generation via Video Diffusion Models, Yu et al., Arxiv 2024\n\n[📄 Paper](https://arxiv.org/abs/2406.07472) | [🌐 Project Page](https://snap-research.github.io/4Real/)\n\nVidu4D: Single Generated Video to High-Fidelity 4D Reconstruction with Dynamic Gaussian Surfels, Wang et al., Arxiv 2024\n\n[📄 Paper](https://arxiv.org/abs/2405.16822) | [🌐 Project Page](https://vidu4d-dgs.github.io/)\n\n## 4D Editing\n\nInstruct 4D-to-4D: Editing 4D Scenes as Pseudo-3D Scenes Using 2D Diffusion, Mou et al., CVPR 2024\n\n[📄 Paper](https://arxiv.org/abs/2406.09402) | [🌐 Project Page](https://immortalco.github.io/Instruct-4D-to-4D/)\n\n## Physics\n\nSync4D: Video Guided Controllable Dynamics for Physics-Based 4D Generation, Fu et al., Arxiv 2024\n\n[📄 Paper](https://arxiv.org/abs/2405.16849) | [🌐 Project Page](https://sync4dphys.github.io/)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcwchenwang%2Fawesome-4d-generation","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcwchenwang%2Fawesome-4d-generation","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcwchenwang%2Fawesome-4d-generation/lists"}