3 papers
cs.CV2025
Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning
Chun-Mei Feng, Kai Yu, Xinxing Xu +4
Benefited from image-text contrastive learning, pre-trained vision-language models, e.g., CLIP, allow to direct leverage texts as images (TaI) for parameter-efficient fine-tuning (…
cs.CV2024
Diffusion-Enhanced Test-time Adaptation with Text and Image Augmentation
Chun-Mei Feng, Yuanyang He, Jian Zou +6
Existing test-time prompt tuning (TPT) methods focus on single-modality data, primarily enhancing images and using confidence ratings to filter out inaccurate images. However, whil…
cs.CV2024
Class Balance Matters to Active Class-Incremental Learning
Zitong Huang, Ze Chen, Yuanze Li +6
Few-Shot Class-Incremental Learning has shown remarkable efficacy in efficient learning new concepts with limited annotations. Nevertheless, the heuristic few-shot annotations may…