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Task-State Adaptation with Prototype Memory for Multi-Task Dense Prediction
Yangyang Xu, Haobo Yuan, Yuzhu Wang +4
Vision foundation backbones provide strong representations for dense prediction, yet a single shared feature still needs to support tasks with different, image-dependent adaptation…
-control: Training-Free Camera Control via Block-Conditional Gibbs Refinement
Yuzhu Wang, Xi Ye, Duo Su +2
Training-free camera control for pretrained flow-matching video generators is a partial-observation inverse problem: a depth-warped guidance video supplies noisy evidence on a subs…
Attention to the Burstiness in Visual Prompt Tuning!
Yuzhu Wang, Manni Duan, Shu Kong
Visual Prompt Tuning (VPT) is a parameter-efficient fune-tuning technique that adapts a pre-trained vision Transformer (ViT) by learning a small set of parameters in the input spac…
Revisiting the Power of Prompt for Visual Tuning
Yuzhu Wang, Lechao Cheng, Chaowei Fang +3
Visual prompt tuning (VPT) is a promising solution incorporating learnable prompt tokens to customize pre-trained models for downstream tasks. However, VPT and its variants often e…