Object Detection

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445 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 test-dev	Cascade Mask R-CNN (Triple-ResNeXt152, multi-scale)	CBNet: A Novel Composite Backbone Network Architecture for Object Detection	See all
COCO minival	Mask R-CNN (ResNeXt-152-FPN, cascade)	Rethinking ImageNet Pre-training	See all
PASCAL VOC 2007	SNIPER	SNIPER: Efficient Multi-Scale Training	See all
ImageNet Detection	Inception V1	Going Deeper with Convolutions	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
India Driving Dataset	hybrid incremental net	On Generalizing Detection Models for Unconstrained Environments	See all
BDD100k	hybrid incremental net	On Generalizing Detection Models for Unconstrained Environments	See all
COCO 2017	ResNeXt-101	FoveaBox: Beyond Anchor-based Object Detector	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

Subtasks

3D Object Detection

13 leaderboards

38 papers with code

Real-Time Object Detection

2 leaderboards

28 papers with code

Salient Object Detection

6 leaderboards

24 papers with code

Weakly Supervised Object Detection

9 leaderboards

13 papers with code

Video Object Detection

1 leaderboard

8 papers with code

See all 21 subtasks

Greatest papers with code

Searching for MobileNetV3

6 May 2019 • tensorflow/models •

We achieve new state of the art results for mobile classification, detection and segmentation.

#74 best model for Image Classification on ImageNet

IMAGE CLASSIFICATION NEURAL ARCHITECTURE SEARCH OBJECT DETECTION SEMANTIC SEGMENTATION

58,584

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

58,584

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.

#79 best model for Image Classification on ImageNet

IMAGE CLASSIFICATION OBJECT DETECTION SEMANTIC SEGMENTATION

58,584

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.

#32 best model for Object Detection on COCO test-dev

DENSE OBJECT DETECTION

58,584

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.

#86 best model for Image Classification on ImageNet

IMAGE CLASSIFICATION OBJECT DETECTION

58,584

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 test (using extra training data)

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

58,584

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.

#55 best model for Object Detection on COCO test-dev

OBJECT DETECTION

58,584

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.

#7 best model for Semantic Segmentation on Cityscapes val

IMAGE CLASSIFICATION OBJECT DETECTION SEMANTIC SEGMENTATION

58,584

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

58,584

Paper
Code