activity
20232026
most citedSEINE: Short-to-Long Video Diffusion Model for Generative Transition and Prediction

12 citations · 15 across the 17 of their papers we have counts for

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Showing 2025Show all

11 papers · 1 filter

cs.CV2025

UniFlow: A Unified Pixel Flow Tokenizer for Visual Understanding and Generation

Zhengrong Yue, Haiyu Zhang, Xiangyu Zeng +7

Tokenizer is a crucial component for both visual understanding and generation. To advance toward the ultimate goal of universal modeling, recent research has focused on developing…

cs.CV2025

LinearSR: Unlocking Linear Attention for Stable and Efficient Image Super-Resolution

Xiaohui Li, Shaobin Zhuang, Shuo Cao +6

Generative models for Image Super-Resolution (SR) are increasingly powerful, yet their reliance on self-attention's quadratic complexity (O(N^2)) creates a major computational bott…

cs.CV2025

WeTok: Powerful Discrete Tokenization for High-Fidelity Visual Reconstruction

Shaobin Zhuang, Yiwei Guo, Canmiao Fu +7

Visual tokenizer is a critical component for vision generation. However, the existing tokenizers often face unsatisfactory trade-off between compression ratios and reconstruction f…

cs.CV2025

Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin

Fangyikang Wang, Hubery Yin, Lei Qian +9

The diffusion models (DMs) have demonstrated the remarkable capability of generating images via learning the noised score function of data distribution. Current DM sampling techniq…

cs.LG2025

Efficiently Access Diffusion Fisher: Within the Outer Product Span Space

Fangyikang Wang, Hubery Yin, Shaobin Zhuang +7

Recent Diffusion models (DMs) advancements have explored incorporating the second-order diffusion Fisher information (DF), defined as the negative Hessian of log density, into vari…

cs.CV2025

Video-GPT via Next Clip Diffusion

Shaobin Zhuang, Zhipeng Huang, Ying Zhang +6

GPT has shown its remarkable success in natural language processing. However, the language sequence is not sufficient to describe spatial-temporal details in the visual world. Alte…

cs.CV2025

V-Stylist: Video Stylization via Collaboration and Reflection of MLLM Agents

Zhengrong Yue, Shaobin Zhuang, Kunchang Li +2

Despite the recent advancement in video stylization, most existing methods struggle to render any video with complex transitions, based on an open style description of user query.…

cs.CV2025★ 1 cited

TimeStep Master: Asymmetrical Mixture of Timestep LoRA Experts for Versatile and Efficient Diffusion Models in Vision

Shaobin Zhuang, Yiwei Guo, Yanbo Ding +7

Diffusion models have driven the advancement of vision generation over the past years. However, it is often difficult to apply these large models in downstream tasks, due to massiv…

cs.CV2025

WeGen: A Unified Model for Interactive Multimodal Generation as We Chat

Zhipeng Huang, Shaobin Zhuang, Canmiao Fu +7

Existing multimodal generative models fall short as qualified design copilots, as they often struggle to generate imaginative outputs once instructions are less detailed or lack th…

cs.CV2025

Get In Video: Add Anything You Want to the Video

Shaobin Zhuang, Zhipeng Huang, Binxin Yang +7

Video editing increasingly demands the ability to incorporate specific real-world instances into existing footage, yet current approaches fundamentally fail to capture the unique v…

cs.CV2025★ 1 cited

DiffVSR: Revealing an Effective Recipe for Taming Robust Video Super-Resolution Against Complex Degradations

Xiaohui Li, Yihao Liu, Shuo Cao +6

Diffusion models have demonstrated exceptional capabilities in image restoration, yet their application to video super-resolution (VSR) faces significant challenges in balancing fi…