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https://paperswithcode.com/task/object-detection

https://paperswithcode.com/task/object-detection

About

Object detection is the task of detecting instances of objects of a certain class within an image. The state-of-the-art methods can be categorized into two main types: one-stage methods and two stage-methods. One-stage methods prioritize inference speed, and example models include YOLO, SSD and RetinaNet. Two-stage methods prioritize detection accuracy, and example models include Faster R-CNN, Mask R-CNN and Cascade R-CNN.

The most popular benchmark is the MSCOCO dataset. Models are typically evaluated according to a Mean Average Precision metric.

( Image credit: Detectron )

Benchmarks

 

 

TREND

DATASET

BEST METHOD

PAPER TITLE

PAPER

CODE

COMPARE

 

COCO test-dev

 Cascade Eff-B7 NAS-FPN (1280, self-training Copy Paste, single-scale)

Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation

   

See all

 

COCO minival

 Cascade Eff-B7 NAS-FPN (1280, self-training Copy Paste, single-scale)

Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation

   

See all

 

PASCAL VOC 2007

 Cascade Eff-B7 NAS-FPN (Copy Paste pre-training, single-scale)

Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation

   

See all

 

CrowdHuman (full body)

 Beta R-CNN

Beta R-CNN: Looking into Pedestrian Detection from Another Perspective

   

See all

 

KITTI Cars Easy

 Patches

Patch Refinement -- Localized 3D Object Detection

 

 

See all

 

UAVDT

 SpotNet

SpotNet: Self-Attention Multi-Task Network for Object Detection

   

See all

 

KITTI Cars Moderate

 Patches

Patch Refinement -- Localized 3D Object Detection

 

 

See all

 

KITTI Cars Hard

 Patches

Patch Refinement -- Localized 3D Object Detection

 

 

See all

 

WiderPerson

 IterDet (Faster RCNN, ResNet50, 2 iterations)

IterDet: Iterative Scheme for Object Detection in Crowded Environments

   

See all

 

PASCAL VOC 2012

 SSD512 (07+12+COCO)

SSD: Single Shot MultiBox Detector

   

See all

 

Visual Genome

 MSDN

Scene Graph Generation from Objects, Phrases and Region Captions

   

See all

 

nuScenes

 BIRANet(RGB+Radar)

Radar+RGB Attentive Fusion for Robust Object Detection in Autonomous Vehicles

   

See all

 

UA-DETRAC

 SpotNet

SpotNet: Self-Attention Multi-Task Network for Object Detection

   

See all

 

PeopleArt

 Fast R-CNN (VGG16)

Detecting People in Artwork with CNNs

   

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

 

PASCAL Part 2010 - Animals

 Attention-based Joint Detection of Object and Semantic Part

Attention-based Joint Detection of Object and Semantic Part

   

See all

 

SUN-RGBD val

 CDSSD

How To Extract Fashion Trends From Social Media? A Robust Object Detector With Support For Unsupervised Learning

   

See all

 

DOTA

 BBAVector + rh

Oriented Object Detection in Aerial Images with Box Boundary-Aware Vectors

   

See all

 

KITTI Pedestrians Easy

 Vote3Deep

Vote3Deep: Fast Object Detection in 3D Point Clouds Using Efficient Convolutional Neural Networks

 

 

See all

 

KITTI Pedestrians Moderate

 Vote3Deep

Vote3Deep: Fast Object Detection in 3D Point Clouds Using Efficient Convolutional Neural Networks

 

 

See all

 

KITTI Pedestrians Hard

 Vote3Deep

Vote3Deep: Fast Object Detection in 3D Point Clouds Using Efficient Convolutional Neural Networks

 

 

See all

 

KITTI Cyclists Easy

 Vote3Deep

Vote3Deep: Fast Object Detection in 3D Point Clouds Using Efficient Convolutional Neural Networks

 

 

See all

 

KITTI Cyclists Moderate

 Vote3Deep

Vote3Deep: Fast Object Detection in 3D Point Clouds Using Efficient Convolutional Neural Networks

 

 

See all

 

KITTI Cyclists Hard

 Vote3Deep

Vote3Deep: Fast Object Detection in 3D Point Clouds Using Efficient Convolutional Neural Networks

 

 

See all

 

Extragalactic Planetary Nebulae

 PNe within NGC1380 & NGC1404

Fornax 3D project: automated detection of planetary nebulae in the centres of early-type galaxies and first results

   

See all

 

COCO+

 RepPoints + Self-adaptation

Slender Object Detection: Diagnoses and Improvements

   

See all

 

LVIS v1.0

 Eff-B7 NAS-FPN (1280, Copy-Paste pre-training))

Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation

   

See all

 

 

 

 

 

 

 

 

Greatest papers with code

 

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

17 Apr 2017 • tensorflow/tensorflow • 

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

IMAGE CLASSIFICATION OBJECT DETECTION

 154,064
 
 

MobileDets: Searching for Object Detection Architectures for Mobile Accelerators

30 Apr 2020 • tensorflow/models • 

MobileDets also outperform MobileNetV2+SSDLite by 1. 9 mAP on mobile CPUs, 3. 7 mAP on EdgeTPUs and 3. 4 mAP on DSPs while running equally fast.

 

NEURAL ARCHITECTURE SEARCH OBJECT DETECTION

 69,125

 

 

 

 

 

 

posted @ 2021-03-18 10:54  leoking01  阅读(631)  评论(0编辑  收藏  举报
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