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arXiv 1903.00839cs.CVcs.CL

Improving Referring Expression Grounding with Cross-modal Attention-guided Erasing

The Chinese University of Hong Kong(香港中文大学);SenseTime Research(商汤科技研究院)

Xihui Liu, Zihao Wang, Jing Shao, Xiaogang Wang, Hongsheng Li

英文摘要:

Referring expression grounding aims at locating certain objects or persons in an image with a referring expression, where the key challenge is to comprehend and align various types of information from visual and textual domain, such as visual attributes, location and interactions with surrounding regions. Although the attention mechanism has been successfully applied for cross-modal alignments, previous attention models focus on only the most dominant features of both modalities, and neglect the fact that there could be multiple comprehensive textual-visual correspondences between images and referring expressions. To tackle this issue, we design a novel cross-modal attention-guided erasing approach, where we discard the most dominant information from either textual or visual domains to generate difficult training samples online, and to drive the model to discover complementary textual-visual correspondences. Extensive experiments demonstrate the effectiveness of our proposed method, which achieves state-of-the-art performance on three referring expression grounding datasets.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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