Adaptive Two-Stream Consensus Network for Weakly-Supervised Temporal Action Localization-Reference-Cited by-同舟云学术

Adaptive Two-Stream Consensus Network for Weakly-Supervised Temporal Action Localization

Author:

Zhai Yuanhao¹^ORCID,Wang Le¹^ORCID,Tang Wei²^ORCID,Zhang Qilin³^ORCID,Zheng Nanning¹^ORCID,Doermann David⁴^ORCID,Yuan Junsong⁴^ORCID,Hua Gang⁴^ORCID

Affiliation:

1. Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, Shaanxi, China

2. Department of Computer Science, University of Illinois at Chicago, Chicago, IL, USA

3. independent researcher, Menlo Park, CA, USA

4. Wormpex AI Research, Bellevue, WA, USA

Funder

National Key R&D Program of China

Natural Science Foundation of Shaanxi Province

Fundamental Research Funds for the Central Universities

Defense Advanced Research Projects Agency

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Vision and Pattern Recognition,Software

Link

Reference73 articles.

2. Adversarial background-aware loss for weakly-supervised temporal activity localization;min;Proc Eur Conf Comput Vis,2020

5. Learning deep features for discriminative localization;zhou;Proc IEEE Conf Comput Vis Pattern Recognit,2016

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