1 citations · 2 across the 4 of their papers we have counts for
5 papers
WinTok: A Win-Win Hybrid Tokenizer via Decomposing Visual Understanding and Generation with Transferable Tokens
Yiwei Guo, Shaobin Zhuang, Zhipeng Huang +4
Building a unified visual tokenizer is essential for bridging the gap between visual understanding and generation. Yet existing approaches struggle with the inherent conflict betwe…
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…
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…
TransAgent: Transfer Vision-Language Foundation Models with Heterogeneous Agent Collaboration
Yiwei Guo, Shaobin Zhuang, Kunchang Li +2
Vision-language foundation models (such as CLIP) have recently shown their power in transfer learning, owing to large-scale image-text pre-training. However, target domain data in…
GlobalWalk: Learning Global-aware Node Embeddings via Biased Sampling
Zhengrong Xue, Ziao Guo, Yiwei Guo
Popular node embedding methods such as DeepWalk follow the paradigm of performing random walks on the graph, and then requiring each node to be proximate to those appearing along w…