دورية أكاديمية

Background-Click Supervision for Temporal Action Localization.

التفاصيل البيبلوغرافية
العنوان: Background-Click Supervision for Temporal Action Localization.
المؤلفون: Yang, Le, Han, Junwei, Zhao, Tao, Lin, Tianwei, Zhang, Dingwen, Chen, Jianxin
المصدر: IEEE Transactions on Pattern Analysis & Machine Intelligence; Dec2022, Vol. 44 Issue Part3, p9814-9829, 16p
مصطلحات موضوعية: SUPERVISION, ACTIVE learning, VIDEO compression, MARKOV processes, TASK analysis, MATHEMATICAL convolutions
مستخلص: Weakly supervised temporal action localization aims at learning the instance-level action pattern from the video-level labels, where a significant challenge is action-context confusion. To overcome this challenge, one recent work builds an action-click supervision framework. It requires similar annotation costs but can steadily improve the localization performance when compared to the conventional weakly supervised methods. In this paper, by revealing that the performance bottleneck of the existing approaches mainly comes from the background errors, we find that a stronger action localizer can be trained with labels on the background video frames rather than those on the action frames. To this end, we convert the action-click supervision to the background-click supervision and develop a novel method, called BackTAL. Specifically, BackTAL implements two-fold modeling on the background video frames, i.e., the position modeling and the feature modeling. In position modeling, we not only conduct supervised learning on the annotated video frames but also design a score separation module to enlarge the score differences between the potential action frames and backgrounds. In feature modeling, we propose an affinity module to measure frame-specific similarities among neighboring frames and dynamically attend to informative neighbors when calculating temporal convolution. Extensive experiments on three benchmarks are conducted, which demonstrate the high performance of the established BackTAL and the rationality of the proposed background-click supervision. [ABSTRACT FROM AUTHOR]
Copyright of IEEE Transactions on Pattern Analysis & Machine Intelligence is the property of IEEE and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
قاعدة البيانات: Complementary Index
الوصف
تدمد:01628828
DOI:10.1109/TPAMI.2021.3132058