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cs.CV2025
A Generative Data Framework with Authentic Supervision for Underwater Image Restoration and Enhancement
Yufeng Tian, Yifan Chen, Zhe Sun +5
Underwater image restoration and enhancement are crucial for correcting color distortion and restoring image details, thereby establishing a fundamental basis for subsequent underw…
cs.CV2025
Class-Aware Prototype Learning with Negative Contrast for Test-Time Adaptation of Vision-Language Models
Xiaozhen Qiao, Jingkai Zhao, Yuqiu Jiang +4
Vision-Language Models (VLMs) demonstrate impressive zero-shot generalization through large-scale image-text pretraining, yet their performance can drop once the deployment distrib…
cs.CV2025
Bidirectional Prototype-Reward co-Evolution for Test-Time Adaptation of Vision-Language Models
Xiaozhen Qiao, Peng Huang, Jiakang Yuan +6
Test-time adaptation (TTA) is crucial in maintaining performance of Vision Language Models (VLMs) when facing distribution shifts, particularly when the source data or target label…