activity
20242026
collaborators

5 papers

cs.CV2026

Salt: Self-Consistent Distribution Matching with Cache-Aware Training for Fast Video Generation

Xingtong Ge, Yi Zhang, Yushi Huang +6

Distilling video generation models to extremely low inference budgets (e.g., 2--4 NFEs) is crucial for real-time deployment, yet remains challenging. Trajectory-style consistency d…

cs.CV2026

AR-CoPO: Align Autoregressive Video Generation with Contrastive Policy Optimization

Dailan He, Guanlin Feng, Xingtong Ge +5

Streaming autoregressive (AR) video generators combined with few-step distillation achieve low-latency, high-quality synthesis, yet remain difficult to align via reinforcement lear…

cs.CV2026

Improving Joint Audio-Video Generation with Cross-Modal Context Learning

Bingqi Ma, Linlong Lang, Ming Zhang +5

The dual-stream transformer architecture-based joint audio-video generation method has become the dominant paradigm in current research. By incorporating pre-trained video diffusio…

cs.CV2025

Towards Seamless Borders: A Method for Mitigating Inconsistencies in Image Inpainting and Outpainting

Xingzhong Hou, Jie Wu, Boxiao Liu +5

Image inpainting is the task of reconstructing missing or damaged parts of an image in a way that seamlessly blends with the surrounding content. With the advent of advanced genera…

cs.CV2024

See Further When Clear: Curriculum Consistency Model

Yunpeng Liu, Boxiao Liu, Yi Zhang +4

Significant advances have been made in the sampling efficiency of diffusion models and flow matching models, driven by Consistency Distillation (CD), which trains a student model t…