2072 papers with code • 1 benchmarks • 1 datasets

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Use these libraries to find object-detection models and implementations


Most implemented papers

Deep Residual Learning for Image Recognition

tensorflow/models CVPR 2016

Deep residual nets are foundations of our submissions to ILSVRC & COCO 2015 competitions, where we also won the 1st places on the tasks of ImageNet detection, ImageNet localization, COCO detection, and COCO segmentation.

YOLO9000: Better, Faster, Stronger

AlexeyAB/darknet CVPR 2017

On the 156 classes not in COCO, YOLO9000 gets 16. 0 mAP.

YOLOv4: Optimal Speed and Accuracy of Object Detection

AlexeyAB/darknet 23 Apr 2020

There are a huge number of features which are said to improve Convolutional Neural Network (CNN) accuracy.

Focal Loss for Dense Object Detection

facebookresearch/detectron ICCV 2017

Our novel Focal Loss focuses training on a sparse set of hard examples and prevents the vast number of easy negatives from overwhelming the detector during training.

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

rbgirshick/py-faster-rcnn NeurIPS 2015

In this work, we introduce a Region Proposal Network (RPN) that shares full-image convolutional features with the detection network, thus enabling nearly cost-free region proposals.

Mask R-CNN

matterport/Mask_RCNN ICCV 2017

Our approach efficiently detects objects in an image while simultaneously generating a high-quality segmentation mask for each instance.

MMDetection: Open MMLab Detection Toolbox and Benchmark

open-mmlab/mmdetection 17 Jun 2019

In this paper, we introduce the various features of this toolbox.

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

tensorflow/tensorflow 17 Apr 2017

We present a class of efficient models called MobileNets for mobile and embedded vision applications.

You Only Look Once: Unified, Real-Time Object Detection

AlexeyAB/darknet CVPR 2016

A single neural network predicts bounding boxes and class probabilities directly from full images in one evaluation.

CSPNet: A New Backbone that can Enhance Learning Capability of CNN

AlexeyAB/darknet 27 Nov 2019

Neural networks have enabled state-of-the-art approaches to achieve incredible results on computer vision tasks such as object detection.