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- DOI: https://doi.org/10.48550/arXiv.2007.12099
- Authors: Long, Xiang, Deng, Kaipeng, Wang, Guanzhong…
- Published: 2020/07/23
- RelatedEntitiesURL: http://arxiv.org/pdf/2007.12099.pdf
- Subject: Computer Vision and Pattern Recognition (cs.CV)
- Cite As: arXiv:2007.12099 [cs.CV]
Object detection is one of the most important areas in computer vision, which plays a key role in various practical scenarios. Due to limitation of hardware, it is often necessary to sacrifice accuracy to ensure the infer speed of the detector in practice. Therefore, the balance between effectivenes...Explore further
- The PP-YOLO model shows the promise of state of the art object detection, but the improvements are incremental over other object detectors and it is written in a new framework. At this stage, the best thing to do is to develop your own empirical result by training PP-YOLO on your own dataset. (To be notified when you can easily use PP-YOLO on your ...
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[2007.12099] PP-YOLO: An Effective and Efficient …
WEBMar 14, 2024 · PP-YOLO is faster (FPS) and more accurate(COCO mAP) than other state-of-the-art detectors, such as EfficientDet and YOLOv4. In this paper, we explore a lot of …
WEBAug 22, 2020 · PP-YOLO Performance. According to the paper, the PP-YOLO can achieve a mAP of 45.2% COCO dataset which exceeds the 43.5% of YOLO v4. When tested on a V100 with batch size = 1, the PP …
WEBYOLOv4 considers various strate-gies such as bag of freebies and bag of specials on the ba-sis of YOLOv3, which greatly improves the performance of the detector. This paper …
Review of PP-YOLO: An Effective and Efficient …
WEBPP-YOLO stands for PaddlePaddle. YOLO for "You Only Look Once". This framework aims to make building, training, optimizing, and deploying these models for object detection more straightforward and efficient.
WEBAug 18, 2022 · The relative improvement of PP-YOLO (around 100%) is larger than YOLOv4 (around 70%). It is mainly because tensorRT optimizes for ResNet model better than Darknet. PP-YOLO results have...
WEBJul 23, 2020 · By combining multiple tricks, PP-YOLO can achieve a better balance between effectiveness (45.% mAP) and efficiency (72.9 FPS), surpassing the existing state-of-the-art detectors such as...
PP-YOLO: An Effective and Efficient Implementation of Object …
WEBJul 23, 2020 · PP-YOLO, a new object detector based on YOLOv3, achieves a better balance between effectiveness (45.2% mAP) and efficiency (72.9 FPS) than existing …
YOLOv4 Explained | Papers With Code
WEBYOLOv4 is a one-stage object detection model that improves on YOLOv3 with several bags of tricks and modules introduced in the literature. The components section below details …
[2004.10934] YOLOv4: Optimal Speed and Accuracy of Object …
WEBApr 23, 2020 · YOLOv4: Optimal Speed and Accuracy of Object Detection. Alexey Bochkovskiy, Chien-Yao Wang, Hong-Yuan Mark Liao. (Submitted on 23 Apr 2020) …
PP-YOLO: An Effective and Efficient Implementation of Object …
WEBJul 23, 2020 · By combining multiple tricks, PP-YOLO can achieve a better balance between effectiveness (45.2% mAP) and efficiency (72.9 FPS), surpassing the existing …
YOLOv4: Optimal Speed and Accuracy of Object Detection
WEBApr 23, 2020 · YOLOv4: Optimal Speed and Accuracy of Object Detection. There are a huge number of features which are said to improve Convolutional Neural Network (CNN) …
PP-YOLO Explained | Papers With Code
WEBPP-YOLO is an object detector based on YOLOv3. It mainly tries to combine various existing tricks that almost not increase the number of model parameters and FLOPs, to …
WEBImproves YOLOv3’s AP and FPS by 10% and 12%, respectively. The main goal of this work is designing a fast operating speed of an object detector in production systems and opti …
WEBScaled-YOLOv4 can achieve the best trade-off between speed and accuracy, and is able to perform real-time object detection on 15 FPS, 30 FPS, and 60 FPS movies, as well as …
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WEBYOLO has become a central real-time object detection system for robotics, driverless cars, and video monitoring applications. We present a comprehensive analysis of YOLO’s …
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[2104.10419] PP-YOLOv2: A Practical Object Detector - arXiv.org
WEBApr 21, 2021 · By combining multiple effective refinements, we boost PP-YOLO's performance from 45.9% mAP to 49.5% mAP on COCO2017 test-dev. Since a …
RL-Based Sim2Real Enhancements for Autonomous Beach …
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WEBand head [43, 44, 45]. YOLOv4 [2] and YOLOv5 [19] introduce the CSPNet [57] design to replace DarkNet [42], coupled with data augmentation strategies, enhanced PAN, and a …
[2011.08036] Scaled-YOLOv4: Scaling Cross Stage Partial …
WEBNov 16, 2020 · Scaled-YOLOv4: Scaling Cross Stage Partial Network. Chien-Yao Wang, Alexey Bochkovskiy, Hong-Yuan Mark Liao. We show that the YOLOv4 object detection …
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