MOTR: End-to-End Multiple-Object Tracking with Transformer

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MOTR: End-to-End Multiple-Object Tracking with Transformer

7 May 2021

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Papers citing "MOTR: End-to-End Multiple-Object Tracking with Transformer"

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Title
Learning by tracking: Siamese CNN for robust target association Laura Leal-Taixé Cristian Canton Ferrer Konrad Schindler 53 427 0 26 Apr 2016
MOT16: A Benchmark for Multi-Object Tracking Anton Milan Laura Leal-Taixe Ian Reid Stefan Roth Konrad Schindler VOT 146 1,807 0 02 Mar 2016
Simple Online and Realtime Tracking Alex Bewley Zongyuan Ge Lionel Ott F. Ramos B. Upcroft VOT 86 3,102 0 02 Feb 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,322 0 10 Dec 2015
An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition Baoguang Shi X. Bai Cong Yao VLM 213 2,489 0 21 Jul 2015
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks Shaoqing Ren Kaiming He Ross B. Girshick Jian Sun AIMat ObjD 520 62,360 0 04 Jun 2015
Sequence to Sequence Learning with Neural Networks Ilya Sutskever Oriol Vinyals Quoc V. Le AIMat 437 20,568 0 10 Sep 2014
Microsoft COCO: Common Objects in Context Nayeon Lee Michael Maire Serge J. Belongie Lubomir Bourdev Ross B. Girshick James Hays Pietro Perona Deva Ramanan C. L. Zitnick Piotr Dollár ObjD 413 43,777 0 01 May 2014