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.
A novel Knowledge-guided Context Optimization (KgCoOp) is introduced to enhance the generalization ability of the learnable prompt for unseen classes and ...
Prompt tuning is an effective way to adapt the pretrained visual-language model (VLM) to the downstream task using task-related textual tokens.
People also search for
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.
Jun 24, 2022 · Prompt tuning is an effective way to adapt the pretrained visual-language model (VLM) to the downstream task us-.
Visual-Language Prompt Tuning with Knowledge-guided Context Optimization [paper] [code] ... Flamingo: a Visual Language Model for Few-Shot Learning [paper].
People also search for