Real-Time Object Detection

60 papers with code • 3 benchmarks • 8 datasets

Real-time object detection is the task of doing object detection in real-time with fast inference while maintaining a base level of accuracy.

( Image credit: CenterNet )

Greatest papers with code

SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization

tensorflow/models CVPR 2020

We propose SpineNet, a backbone with scale-permuted intermediate features and cross-scale connections that is learned on an object detection task by Neural Architecture Search.

General Classification Image Classification +4

Objects as Points

tensorflow/models 16 Apr 2019

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

Keypoint Detection Real-Time Object Detection

Focal Loss for Dense Object Detection

tensorflow/models 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.

Dense Object Detection Long-tail Learning +2

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.

3D Instance Segmentation Human Part Segmentation +7

R-FCN: Object Detection via Region-based Fully Convolutional Networks

facebookresearch/detectron NeurIPS 2016

In contrast to previous region-based detectors such as Fast/Faster R-CNN that apply a costly per-region subnetwork hundreds of times, our region-based detector is fully convolutional with almost all computation shared on the entire image.

Real-Time Object Detection

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

facebookresearch/detectron 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.

Real-Time Object Detection Region Proposal

YOLOv4: Optimal Speed and Accuracy of Object Detection

pjreddie/darknet 23 Apr 2020

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

Data Augmentation Real-Time Object Detection

Scaled-YOLOv4: Scaling Cross Stage Partial Network

AlexeyAB/darknet CVPR 2021

We show that the YOLOv4 object detection neural network based on the CSP approach, scales both up and down and is applicable to small and large networks while maintaining optimal speed and accuracy.

Real-Time Object Detection