2 citations · 3 across the 13 of their papers we have counts for
5 papers · 1 filter
Parallel Decoding Distillation for Fast Image and Video Generation
Neta Shaul, Chao Liu, Arash Vahdat +1
Generation in video diffusion or flow models is computationally expensive due to the slow and iterative sampling process. Current state-of-the-art (SOTA) acceleration methods heavi…
Flex-Forcing: Towards a Unified Autoregressive and Bidirectional Video Diffusion Model
Xinyin Ma, Julius Berner, Chao Liu +3
Recent progress in large-scale generative models has substantially advanced video generation, yet existing methods remain constrained by a rigid inference paradigm. Bidirectional d…
Mode Seeking meets Mean Seeking for Fast Long Video Generation
Shengqu Cai, Weili Nie, Chao Liu +8
Scaling video generation from seconds to minutes faces a critical bottleneck: while short-video data is abundant and high-fidelity, coherent long-form data is scarce and limited to…
On the Adversarial Robustness of 3D Large Vision-Language Models
Chao Liu, Ngai-Man Cheung
3D Vision-Language Models (VLMs), such as PointLLM and GPT4Point, have shown strong reasoning and generalization abilities in 3D understanding tasks. However, their adversarial rob…
Transition Matching Distillation for Fast Video Generation
Weili Nie, Julius Berner, Nanye Ma +3
Large video diffusion and flow models have achieved remarkable success in high-quality video generation, but their use in real-time interactive applications remains limited due to…