个人信息
教师姓名：何涛
教师拼音名称：hetao
所在单位：智能计算研究院
学历：博士研究生毕业
性别：男
学位：哲学博士学位
职称：副研究员（特聘）
在职信息：在职人员
毕业院校：澳大利亚莫纳什大学
硕士生导师
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所属院系： 机关及其他单位
其他联系方式
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论文成果
Learning from the Scene and Borrowing from the Rich: Tackling the Long Tail in Scene Graph Generation
发布时间：2025-05-23 点击次数：
所属单位：[1] Faculty of Information Technology, Monash University, Australia; [2] Center for Future Media, School of Computer Science and Engineering, University of Electronic Science and Technology of China, China
发表刊物：arXiv
关键字：Machine learning
摘要：Despite the huge progress in scene graph generation in recent years, its long-tail distribution in object relationships remains a challenging and pestering issue. Existing methods largely rely on either external knowledge or statistical bias information to alleviate this problem. In this paper, we tackle this issue from another two aspects: (1) scene-object interaction aiming at learning specific knowledge from a scene via an additive attention mechanism; and (2) long-tail knowledge transfer which tries to transfer the rich knowledge learned from the head into the tail. Extensive experiments on the benchmark dataset Visual Genome on three tasks demonstrate that our method outperforms current state-of-the-art competitors. Copyright ? 2020, The Authors. All rights reserved.
文献类型：Preprint (PP)
是否译文：否
