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Exploring Sparse Visual Prompt for Domain Adaptive Dense Prediction
April 16, 2024, 4:48 a.m. | Senqiao Yang, Jiarui Wu, Jiaming Liu, Xiaoqi Li, Qizhe Zhang, Mingjie Pan, Yulu Gan, Zehui Chen, Shanghang Zhang
cs.CV updates on arXiv.org arxiv.org
Abstract: The visual prompts have provided an efficient manner in addressing visual cross-domain problems. In previous works, Visual Domain Prompt (VDP) first introduces domain prompts to tackle the classification Test-Time Adaptation (TTA) problem by warping image-level prompts on the input and fine-tuning prompts for each target domain. However, since the image-level prompts mask out continuous spatial details in the prompt-allocated region, it will suffer from inaccurate contextual information and limited domain knowledge extraction, particularly when dealing …
abstract arxiv classification cs.cv domain fine-tuning image prediction prompt prompts test type visual
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