Self-Supervised Visual Feature Learning With Deep Neural Networks: A Survey

IEEE Transactions on Pattern Analysis and Machine Intelligence(2021)

引用 1836|浏览3319
暂无评分
摘要
Large-scale labeled data are generally required to train deep neural networks in order to obtain better performance in visual feature learning from images or videos for computer vision applications. To avoid extensive cost of collecting and annotating large-scale datasets, as a subset of unsupervised learning methods, self-supervised learning methods are proposed to learn general image and video f...
更多
查看译文
关键词
Task analysis,Visualization,Videos,Training,Learning systems,Feature extraction,Annotations
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要