CLIP-VG: Self-Paced Curriculum Adapting of CLIP for Visual Grounding

• Published in: IEEE transactions on multimedia Vol. 26; pp. 4334 - 4347
• Main Authors: Xiao, Linhui, Yang, Xiaoshan, Peng, Fang, Yan, Ming, Wang, Yaowei, Xu, Changsheng
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptation models; Algorithms; and vision-language models; Annotations; Curricula; curriculum learning; Data models; Grounding; Labels; pseudo-language label; Reliability; Task analysis; Vision; Visual fields; Visual grounding; Visualization

Visual Grounding (VG) is a crucial topic in the field of vision and language, which involves locating a specific region described by expressions within an image. To reduce the reliance on manually labeled data, unsupervised methods have been developed to locate regions using pseudo-labels. However,...