Mar 23, 2023 · Abstract:Prompt tuning is an effective way to adapt the pre-trained visual-language model (VLM) to the downstream task using task-related ...
Prompt tuning is an effective way to adapt the pretrained visual-language model (VLM) to the downstream task us- ing task-related textual tokens.
We introduce a novel Knowledge-guided Context Optimization (KgCoOp) to enhance the generalization ability of the learnable prompt for unseen classes.
Prompt tuning is an effective way to adapt the pretrained visual-language model (VLM) to the downstream task using task-related textual tokens.
Prompt tuning is an effective way to adapt the pretrained visual-language model (VLM) to the downstream task using task-related textual tokens.
A novel Knowledge-guided Context Optimization (KgCoOp) is introduced to enhance the generalization ability of the learnable prompt for unseen classes and ...
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It can effectively model textual context and replenish the video category description. Simultaneously, building upon insights from (Yao, Zhang, ...
Prompt tuning is an effective way to adapt the pre-trained visual-language model (VLM) to the downstream task using task-related textual tokens.
Mar 23, 2023 · Formally, we propose a novel prompt tuning method named Knowledge-guided Context. Optimization (KgCoOp) to infer learnable prompts which have a ...
Sep 3, 2023 · Bibliographic details on Visual-Language Prompt Tuning with Knowledge-guided Context Optimization.
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