End-to-End Video Object Detection with Spatial-Temporal Transformers
Author:
Affiliation:
1. Shanghai Jiao Tong University, Shanghai, China
2. Peking University, Beijing, China
3. Sensetime Research, Shanghai, China
4. University of California, Los Angeles, Los Angeles, CA, USA
Funder
National Natural Science Foundation of China
Shanghai Municipal Science and Technology Major Project
National Key Research and Development Program of China
Zhejiang Lab
National Key R&D Program of China
Shanghai Science and Technology RD Program of China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3474085.3475285
Reference61 articles.
1. Hatem Belhassen Heng Zhang Virginie Fresse and El-Bay Bourennane. 2019. Improving Video Object Detection by Seq-Bbox Matching. In VISIGRAPP (5: VISAPP). 226--233. Hatem Belhassen Heng Zhang Virginie Fresse and El-Bay Bourennane. 2019. Improving Video Object Detection by Seq-Bbox Matching. In VISIGRAPP (5: VISAPP). 226--233.
2. Gedas Bertasius Lorenzo Torresani and Jianbo Shi. 2018. Object Detection in Video with Spatiotemporal Sampling Networks. In ECCV. 342--357. Gedas Bertasius Lorenzo Torresani and Jianbo Shi. 2018. Object Detection in Video with Spatiotemporal Sampling Networks. In ECCV. 342--357.
3. Yihong Chen Yue Cao Han Hu and Liwei Wang. 2020. Memory enhanced global-local aggregation for video object detection. In CVPR. 10337--10346. Yihong Chen Yue Cao Han Hu and Liwei Wang. 2020. Memory enhanced global-local aggregation for video object detection. In CVPR. 10337--10346.
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