Object Detection

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392 papers with code · Computer Vision

Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos.

State-of-the-art leaderboards

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Dataset	Best Method	Paper title	Compare
COCO	HTC + DCN + ResNeXt-101-FPN	Hybrid Task Cascade for Instance Segmentation	See all
PASCAL VOC 2007	SNIPER	SNIPER: Efficient Multi-Scale Training	See all
ImageNet Detection	Inception V1	Going Deeper with Convolutions	See all
PeopleArt	Fast R-CNN (VGG16)	Detecting People in Artwork with CNNs	See all
Visual Genome	MSDN	Scene Graph Generation from Objects, Phrases and Region Captions	See all
COCO 2015	SSD300	SSD: Single Shot MultiBox Detector	See all
Caltech Lanes Cordova	ca	Saliency Optimization from Robust Background Detection	See all
SIXray	YOLO	Evaluation of a Dual Convolutional Neural Network Architecture for Object-wise Anomaly Detection in Cluttered X-ray Security Imagery	See all

Subtasks

3D Object Detection

12 leaderboards

31 papers with code

Real-Time Object Detection

2 leaderboards

25 papers with code

Salient Object Detection

6 leaderboards

20 papers with code

Weakly Supervised Object Detection

9 leaderboards

13 papers with code

Object Proposal Generation

1 leaderboard

7 papers with code

See all 19 subtasks

Greatest papers with code

Looking Fast and Slow: Memory-Guided Mobile Video Object Detection

25 Mar 2019 • tensorflow/models •

Models and examples built with TensorFlow

OBJECT RECOGNITION VIDEO OBJECT DETECTION

56,776

Paper
Code

Pooling Pyramid Network for Object Detection

9 Jul 2018 • tensorflow/models •

We share box predictors across all scales, and replace convolution between scales with max pooling.

OBJECT DETECTION

56,776

Paper
Code

MobileNetV2: Inverted Residuals and Linear Bottlenecks

CVPR 2018 • tensorflow/models •

In this paper we describe a new mobile architecture, MobileNetV2, that improves the state of the art performance of mobile models on multiple tasks and benchmarks as well as across a spectrum of different model sizes.

#66 best model for Image Classification on ImageNet

IMAGE CLASSIFICATION OBJECT DETECTION SEMANTIC SEGMENTATION

56,776

Paper
Code

Focal Loss for Dense Object Detection

ICCV 2017 • tensorflow/models •

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.

#28 best model for Object Detection on COCO

DENSE OBJECT DETECTION

56,776

Paper
Code

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

17 Apr 2017 • tensorflow/models •

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

#73 best model for Image Classification on ImageNet

IMAGE CLASSIFICATION OBJECT DETECTION

56,776

Paper
Code

Mask R-CNN

ICCV 2017 • tensorflow/models •

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

SOTA for Instance Segmentation on Cityscapes (using extra training data)

HUMAN PART SEGMENTATION INSTANCE SEGMENTATION KEYPOINT DETECTION MULTI-HUMAN PARSING OBJECT DETECTION SEMANTIC SEGMENTATION

56,776

Paper
Code

Speed/accuracy trade-offs for modern convolutional object detectors

CVPR 2017 • tensorflow/models •

The goal of this paper is to serve as a guide for selecting a detection architecture that achieves the right speed/memory/accuracy balance for a given application and platform.

#39 best model for Object Detection on COCO

OBJECT DETECTION

56,776

Paper
Code

Deep Residual Learning for Image Recognition

CVPR 2016 • tensorflow/models •

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.

#11 best model for Object Detection on PASCAL VOC 2007

IMAGE CLASSIFICATION OBJECT DETECTION

56,776

Paper
Code

Going Deeper with Convolutions

CVPR 2015 • tensorflow/models •

We propose a deep convolutional neural network architecture codenamed "Inception", which was responsible for setting the new state of the art for classification and detection in the ImageNet Large-Scale Visual Recognition Challenge 2014 (ILSVRC 2014).

SOTA for Object Detection on ImageNet Detection

IMAGE CLASSIFICATION OBJECT DETECTION OBJECT RECOGNITION

56,776

Paper
Code