MaxpoolNMS: Getting Rid of NMS Bottlenecks in Two-Stage Object Detectors-Reference-Cited by-同舟云学术

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MaxpoolNMS: Getting Rid of NMS Bottlenecks in Two-Stage Object Detectors

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

Cai Lile,Zhao Bin,Wang Zhe,Lin Jie,Foo Chuan Sheng,Aly Mohamed Sabry,Chandrasekhar Vijay

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8938205/8953184/08953512.pdf?arnumber=8953512

Cited by 17 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. An Empirical Analysis of Range for 3D Object Detection;2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW);2023-10-02

2. Deep Learning object detection models: evolution and evaluation;Proceedings of the 15th International Conference on Digital Image Processing;2023-05-19

3. Deep learning based object detection for resource constrained devices: Systematic review, future trends and challenges ahead;Neurocomputing;2023-04

4. Enhancing Pedestrian Group Detection and Tracking Through Zone-Based Clustering;IEEE Access;2023

5. Confluence: A Robust Non-IoU Alternative to Non-Maxima Suppression in Object Detection;IEEE Transactions on Pattern Analysis and Machine Intelligence;2023

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