From the 1 of 12 linked papers with an AI index.
5 papers · 1 filter
U-shaped Multi-granularity Learning for Vision-Language Models
Biao Chen, Yunqian Yu, Xiangxu Zhao +3
The paper introduces UPrompt, a U‑shaped multi‑granularity prompt learning framework that combines global and local prompts for vision‑language models, improving fine‑grained seman…
Dropout Prompt Learning: Towards Robust and Adaptive Vision-Language Models
Biao Chen, Lin Zuo, Mengmeng Jing +2
Dropout is a widely used regularization technique which improves the generalization ability of a model by randomly dropping neurons. In light of this, we propose Dropout Prompt Lea…
SWAT: Sliding Window Adversarial Training for Gradual Domain Adaptation
Zixi Wang, Xiangxu Zhao, Tonglan Xie +2
Domain shifts are critical issues that harm the performance of machine learning. Unsupervised Domain Adaptation (UDA) mitigates this issue but suffers when the domain shifts are st…
A Semantic-Enhanced Heterogeneous Graph Learning Method for Flexible Objects Recognition
Kunshan Yang, Wenwei Luo, Yuguo Hu +3
Flexible objects recognition remains a significant challenge due to its inherently diverse shapes and sizes, translucent attributes, and subtle inter-class differences. Graph-based…
Flexible ViG: Learning the Self-Saliency for Flexible Object Recognition
Lin Zuo, Kunshan Yang, Xianlong Tian +3
Existing computer vision methods mainly focus on the recognition of rigid objects, whereas the recognition of flexible objects remains unexplored. Recognizing flexible objects pose…