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Use these libraries to find Object models and implementations
32 papers
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Most implemented papers

YOLO9000: Better, Faster, Stronger

AlexeyAB/darknet CVPR 2017

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

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.

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.

SSD: Single Shot MultiBox Detector

weiliu89/caffe 8 Dec 2015

Experimental results on the PASCAL VOC, MS COCO, and ILSVRC datasets confirm that SSD has comparable accuracy to methods that utilize an additional object proposal step and is much faster, while providing a unified framework for both training and inference.

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

tensorflow/models ICCV 2017

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

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.

Feature Pyramid Networks for Object Detection

PaddlePaddle/PaddleOCR CVPR 2017

Feature pyramids are a basic component in recognition systems for detecting objects at different scales.

FCOS: Fully Convolutional One-Stage Object Detection

tianzhi0549/FCOS ICCV 2019

By eliminating the predefined set of anchor boxes, FCOS completely avoids the complicated computation related to anchor boxes such as calculating overlapping during training.

Objects as Points

xingyizhou/CenterNet 16 Apr 2019

We model an object as a single point --- the center point of its bounding box.