most citedDCRNN: A Deep Cross approach based on RNN for Partial Parameter Sharing in Multi-task Learning

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cs.CV2024

Calibrated Cache Model for Few-Shot Vision-Language Model Adaptation

Kun Ding, Qiang Yu, Haojian Zhang +2

Cache-based approaches stand out as both effective and efficient for adapting vision-language models (VLMs). Nonetheless, the existing cache model overlooks three crucial aspects.…

cs.CV2024

Weak Distribution Detectors Lead to Stronger Generalizability of Vision-Language Prompt Tuning

Kun Ding, Haojian Zhang, Qiang Yu +3

We propose a generalized method for boosting the generalization ability of pre-trained vision-language models (VLMs) while fine-tuning on downstream few-shot tasks. The idea is rea…

cs.CV2024

Compositional Kronecker Context Optimization for Vision-Language Models

Kun Ding, Xiaohui Li, Qiang Yu +3

Context Optimization (CoOp) has emerged as a simple yet effective technique for adapting CLIP-like vision-language models to downstream image recognition tasks. Nevertheless, learn…