5 papers
End-to-End Training for Autoregressive Video Diffusion via Self-Resampling
Yuwei Guo, Ceyuan Yang, Hao He +5
Autoregressive video diffusion models hold promise for world simulation but are vulnerable to exposure bias arising from the train-test mismatch. While recent works address this vi…
S2Accompanist: A Semantic-Aware and Structure-Guided Diffusion Model for Music Accompaniment Generation
Huakang Chen, Wenkai Cheng, Guobin Ma +7
High-fidelity text-to-music generation typically relies on massive proprietary datasets and immense computational resources. Existing models often struggle to generate coherent pur…
SeedVR2: One-Step Video Restoration via Diffusion Adversarial Post-Training
Jianyi Wang, Shanchuan Lin, Zhijie Lin +10
Recent advances in diffusion-based video restoration (VR) demonstrate significant improvement in visual quality, yet yield a prohibitive computational cost during inference. While…
SeedVR: Seeding Infinity in Diffusion Transformer Towards Generic Video Restoration
Jianyi Wang, Zhijie Lin, Meng Wei +5
Video restoration poses non-trivial challenges in maintaining fidelity while recovering temporally consistent details from unknown degradations in the wild. Despite recent advances…
CameraCtrl II: Dynamic Scene Exploration via Camera-controlled Video Diffusion Models
Hao He, Ceyuan Yang, Shanchuan Lin +7
This paper introduces CameraCtrl II, a framework that enables large-scale dynamic scene exploration through a camera-controlled video diffusion model. Previous camera-conditioned v…