1 citations · 1 across the 6 of their papers we have counts for
6 papers
Multi-Grid Post-Training for Long-Form Multi-Shot Video Generation
Jiawei Mao, Haoqin Tu, Hardy Chen +8
Generating long-form multi-shot videos requires coherent within-shot motion and visually consistent narratives across shots. Existing video generators favor continuous motion and s…
VisualClaw: A Real-Time, Personalized Agent for the Physical World
Haoqin Tu, Jianwen Chen, Zijun Wang +14
Vision language models are serving as general-purpose interfaces for complex multimodal tasks. However, deployment still faces three gaps: VLMs typically incur high latency and cos…
Improving Rectified Flow with Boundary Conditions
Xixi Hu, Runlong Liao, Keyang Xu +5
Rectified Flow offers a simple and effective approach to high-quality generative modeling by learning a velocity field. However, we identify a limitation in directly modeling the v…
AMO Sampler: Enhancing Text Rendering with Overshooting
Xixi Hu, Keyang Xu, Bo Liu +2
Achieving precise alignment between textual instructions and generated images in text-to-image generation is a significant challenge, particularly in rendering written text within…
Greedy Growing Enables High-Resolution Pixel-Based Diffusion Models
Cristina N. Vasconcelos, Abdullah Rashwan, Austin Waters +22
We address the long-standing problem of how to learn effective pixel-based image diffusion models at scale, introducing a remarkably simple greedy growing method for stable trainin…
Inflation with Diffusion: Efficient Temporal Adaptation for Text-to-Video Super-Resolution
Xin Yuan, Jinoo Baek, Keyang Xu +2
We propose an efficient diffusion-based text-to-video super-resolution (SR) tuning approach that leverages the readily learned capacity of pixel level image diffusion model to capt…