Tracking by Animation: Unsupervised Learning of Multi-Object Attentive Trackers-Reference-Cited by-同舟云学术

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Tracking by Animation: Unsupervised Learning of Multi-Object Attentive Trackers

Published:2019-06 Issue: Volume: Page:
ISSN:
Container-title:2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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Author:

He Zhen,Li Jian,Liu Daxue,He Hangen,Barber David

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8938205/8953184/08953199.pdf?arnumber=8953199

Cited by 23 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Unsupervised Object-Centric Learning From Multiple Unspecified Viewpoints;IEEE Transactions on Pattern Analysis and Machine Intelligence;2024-05

2. Deep learning and multi-modal fusion for real-time multi-object tracking: Algorithms, challenges, datasets, and comparative study;Information Fusion;2024-05

3. An improved target tracking method based on extraction of corner points;The Visual Computer;2024-03-30

4. Spatial redundancy transformer for self-supervised fluorescence image denoising;2023-06-05

5. Lane-Level and Full-Cycle Multivehicle Tracking Using Low-Channel Roadside LiDAR;IEEE Transactions on Instrumentation and Measurement;2023

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