OmniDirector: General Multi-Shot Camera Cloning without Cross-Paired Data
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Abstract (arXiv)
Cloning camera motion from reference videos is an important task in video generation, as videos provide intuitive and precise control. Existing methods either directly use parametric representations that fail to handle multi-shot generation or synthesize cross-paired data, which suffer from data scarcity, resulting in poor performance in complicated camera motion cloning. To address these issues, we introduce a general camera motion representation that encodes cameras as grid motion videos. This camera grid represents the camera parameters visually and supports the integration of diverse trajectories for multi-shot video generation. Building upon this, we propose OmniDirector, a unified framework trained on a million-scale camera grid-video pairs that coordinates characters, actions, and cameras to provide director-level control for multimodal diffusion transformers. Furthermore, we design a novel hierarchical prompt expansion agent that harmoniously integrates different control signals by systematically describing camera motion and visual content through understanding signal relationships. Extensive experiments demonstrate the superior performance and outstanding controllability of our framework. Project page: https://ymlinfeng.github.io/OmniDirector.github.io/
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 30 of its 39 references that are in the map. First posted on arXiv 11 Jun 2026.
Builds on
30 of 39 references.
References · 30
- 2020Denoising Diffusion Probabilistic Modelscited by 20,851
- 2023Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasetscited by 2,526
- 2022Imagen Video: High Definition Video Generation with Diffusion Modelscited by 1,765
- 2022Make-A-Video: Text-to-Video Generation without Text-Video Datacited by 1,725
- 2023Animate Anyone: Consistent and Controllable Image-to-Video Synthesis for Character Animationcited by 683
- 2025Depth Anything 3: Recovering the Visual Space from Any Viewscited by 626
- 2023MotionCtrl: A Unified and Flexible Motion Controller for Video Generationcited by 568
- 2024Latte: Latent Diffusion Transformer for Video Generationcited by 536
- 2023DynamiCrafter: Animating Open-domain Images with Video Diffusion Priorscited by 463
- 2023VideoComposer: Compositional Video Synthesis with Motion Controllabilitycited by 461
- 2024Lumiere: A Space-Time Diffusion Model for Video Generationcited by 450
- 2024CameraCtrl: Enabling Camera Control for Text-to-Video Generationcited by 448
18 more
- 2023I2VGen-XL: High-Quality Image-to-Video Synthesis via Cascaded Diffusion Modelscited by 343
- 2025MapAnything: Universal Feed-Forward Metric 3D Reconstructioncited by 295
- 2025ReCamMaster: Camera-Controlled Generative Rendering from A Single Videocited by 278
- 2023SEINE: Short-to-Long Video Diffusion Model for Generative Transition and Predictioncited by 231
- 2020TransNet V2: An effective deep network architecture for fast shot transition detectioncited by 166
- 2024CamCo: Camera-Controllable 3D-Consistent Image-to-Video Generationcited by 163
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- 2024ConsistI2V: Enhancing Visual Consistency for Image-to-Video Generationcited by 130
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- 2025CineMaster: A 3D-Aware and Controllable Framework for Cinematic Text-to-Video Generationcited by 73
- 2024MotionMaster: Training-free Camera Motion Transfer For Video Generationcited by 50
- 2024Director3D: Real-world Camera Trajectory and 3D Scene Generation from Textcited by 50
- 2023Control-A-Video: Controllable Text-to-Video Diffusion Models with Motion Prior and Reward Feedback Learningcited by 46
- 2025CamCloneMaster: Enabling Reference-based Camera Control for Video Generationcited by 44
- 2025MultiShotMaster: A Controllable Multi-Shot Video Generation Frameworkcited by 33
- 2025CineTrans: Learning to Generate Videos with Cinematic Transitions via Masked Diffusion Modelscited by 26
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Built on by
Citing papers per year: 2026: 6.
6 papers.
- 2026Decoupling Semantics from Distortions: Multi-Scale Two-Stream Vision-Language Alignment for AI-Generated Image Quality Assessmentcited by 4
- 2026OmniDrive: An LLM-Choreographed Multi-Agent World Model with Unified Latent Co-Compression for Multi-View Driving Video Generationcited by 2
- 2026ParaScale: Scale-Calibrated Camera-Motion Transfer via a Gauge-Invariant Parallax Numbercited by 2
- 2026OrthoMotion:Disentangling Camera and Subject Motion via Geometry Semantics Orthogonal Attentioncited by 1
- 2026TARS: Timestep-Aware Data Scaling for 3D-Free Video Re-Shootingcited by 0
- 2026Proxy2World: Learning to Generate Worlds From Lightweight Proxies without Seeing Themcited by 0
- 2026Proxy2World: Learning to Generate Worlds From Lightweight Proxies without Seeing Them28 Sep 2026
- 2026TARS: Timestep-Aware Data Scaling for 3D-Free Video Re-Shooting30 Jul 2026
- 2026OrthoMotion:Disentangling Camera and Subject Motion via Geometry Semantics Orthogonal Attention22 Jun 2026
- 2026ParaScale: Scale-Calibrated Camera-Motion Transfer via a Gauge-Invariant Parallax Number18 Jun 2026
- 2026OmniDrive: An LLM-Choreographed Multi-Agent World Model with Unified Latent Co-Compression for Multi-View Driving Video Generation16 Jun 2026
- 2026Decoupling Semantics from Distortions: Multi-Scale Two-Stream Vision-Language Alignment for AI-Generated Image Quality Assessment15 Jun 2026
Similar, not cited
Close in wording, no citation either way
- 2025OmniCam: Unified Multimodal Video Generation via Camera Control
- 2025OmniView: An All-Seeing Diffusion Model for 3D and 4D View Synthesis
- 2024AC3D: Analyzing and Improving 3D Camera Control in Video Diffusion Transformers
- 2024OmniDrag: Enabling Motion Control for Omnidirectional Image-to-Video Generation
- 2024Grid: Omni Visual Generation
- 2025OmniV2V: Versatile Video Generation and Editing via Dynamic Content Manipulation
- 2026ActCam: Zero-Shot Joint Camera and 3D Motion Control for Video Generation
- 2024Direct-a-Video: Customized Video Generation with User-Directed Camera Movement and Object Motion