Streaming Video Generation with Streaming Force Control
Not on the map. Why?
Abstract (arXiv)
We introduce StreamForce, a streaming video generation framework that enables physically grounded control through continuous force inputs. Unlike prior video models that train separate models for different force types, assume fixed forces, or rely on non-causal processing, StreamForce is a causal and unified model that responds instantly and coherently to both local and global, time-varying forces. To achieve this, we design a unified force representation as a control signal and develop a distillation pipeline for force-controllable video generation. Our model combines autoregressive efficiency with force responsiveness, sustaining stable photometric and dynamic realism. StreamForce runs at up to 16.6 FPS on a single GPU, achieving state-of-the-art performance in both force adherence and motion realism. Project website: https://neu-vi.github.io/StreamForce/
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 73 of its 83 references that are in the map. First posted on arXiv 5 Jun 2026.
Builds on
73 of 83 references.
References · 73
- 2022Scalable Diffusion Models with Transformerscited by 5,931
- 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,466
- 2022Flow Matching for Generative Modelingcited by 5,426
- 2022Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flowcited by 3,550
- 2025Wan: Open and Advanced Large-Scale Video Generative Modelscited by 2,536
- 2025Qwen3-VL Technical Reportcited by 2,534
- 2023Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasetscited by 2,526
- 2024CogVideoX: Text-to-Video Diffusion Models with An Expert Transformercited by 2,198
- 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
- 2024HunyuanVideo: A Systematic Framework For Large Video Generative Modelscited by 1,597
- 2023Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Modelscited by 1,465
38 more
- 2023One-step Diffusion with Distribution Matching Distillationcited by 978
- 2022CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformerscited by 973
- 2024Genie: Generative Interactive Environmentscited by 706
- 2021VideoGPT: Video Generation using VQ-VAE and Transformerscited by 651
- 2024Improved Distribution Matching Distillation for Fast Image Synthesiscited by 648
- 2024Movie Gen: A Cast of Media Foundation Modelscited by 614
- 2025Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusioncited by 569
- 2023MotionCtrl: A Unified and Flexible Motion Controller for Video Generationcited by 568
- 2024LTX-Video: Realtime Video Latent Diffusioncited by 549
- 2023VideoPoet: A Large Language Model for Zero-Shot Video Generationcited by 479
- 2024CameraCtrl: Enabling Camera Control for Text-to-Video Generationcited by 448
- 2024CAT3D: Create Anything in 3D with Multi-View Diffusion Modelscited by 425
- 2024From Slow Bidirectional to Fast Autoregressive Video Diffusion Modelscited by 401
- 2023PhysGaussian: Physics-Integrated 3D Gaussians for Generative Dynamicscited by 368
- 2023Photorealistic Video Generation with Diffusion Modelscited by 304
- 2025ReCamMaster: Camera-Controlled Generative Rendering from A Single Videocited by 278
- 2024Navigation World Modelscited by 262
- 2025LongLive: Real-time Interactive Long Video Generationcited by 237
- 2026LTX-2: Efficient Joint Audio-Visual Foundation Modelcited by 213
- 2025Rolling Forcing: Autoregressive Long Video Diffusion in Real Timecited by 209
- 2024WonderWorld: Interactive 3D Scene Generation from a Single Imagecited by 197
- 2019Scaling Autoregressive Video Modelscited by 189
- 2024PhysDreamer: Physics-Based Interaction with 3D Objects via Video Generationcited by 185
- 2024Motion Prompting: Controlling Video Generation with Motion Trajectoriescited by 176
- 2025Matrix-game 2.0: An open-source real-time and streaming interactive world modelcited by 174
- 2024PhysGen: Rigid-Body Physics-Grounded Image-to-Video Generationcited by 169
- 2024Direct-a-Video: Customized Video Generation with User-Directed Camera Movement and Object Motioncited by 167
- 2024CAT4D: Create Anything in 4D with Multi-View Video Diffusion Modelscited by 160
- 2024VD3D: Taming Large Video Diffusion Transformers for 3D Camera Controlcited by 156
- 2025Do generative video models understand physical principles?cited by 151
- 2024SV4D: Dynamic 3D Content Generation with Multi-Frame and Multi-View Consistencycited by 143
- 2025Phantom: Subject-consistent video generation via cross-modal alignmentcited by 126
- 2024CamI2V: Camera-Controlled Image-to-Video Diffusion Modelcited by 115
- 2024Loong: Generating Minute-level Long Videos with Autoregressive Language Modelscited by 99
- 2025Hunyuan-GameCraft: High-dynamic Interactive Game Video Generation with Hybrid History Conditioncited by 92
- 2025PhysTwin: Physics-Informed Reconstruction and Simulation of Deformable Objects from Videoscited by 78
- 2024Physics3D: Learning Physical Properties of 3D Gaussians via Video Diffusioncited by 76
- 2025SkyReels-A2: Compose Anything in Video Diffusion Transformerscited by 72
50 most cited of 73 All 73 (JSON)
Built on by
Citing papers per year: 2026: 1.
1 paper.