About

Object recognition is a computer vision technique for detecting + classifying objects in images or videos. Since this is a combined task of object detection plus image classification, the state-of-the-art tables are recorded for each component task here and here.

( Image credit: Tensorflow Object Detection API )

Benchmarks

TREND DATASET BEST METHOD PAPER TITLE PAPER CODE COMPARE

Subtasks

Datasets

Greatest papers with 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).

IMAGE CLASSIFICATION OBJECT DETECTION OBJECT RECOGNITION

GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond

25 Apr 2019open-mmlab/mmdetection

In this paper, we take advantage of this finding to create a simplified network based on a query-independent formulation, which maintains the accuracy of NLNet but with significantly less computation.

INSTANCE SEGMENTATION OBJECT DETECTION OBJECT RECOGNITION

Densely Connected Convolutional Networks

CVPR 2017 pytorch/vision

Recent work has shown that convolutional networks can be substantially deeper, more accurate, and efficient to train if they contain shorter connections between layers close to the input and those close to the output.

BREAST TUMOUR CLASSIFICATION CROWD COUNTING IMAGE CLASSIFICATION OBJECT RECOGNITION PEDESTRIAN ATTRIBUTE RECOGNITION PERSON RE-IDENTIFICATION

DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition

6 Oct 2013jetpacapp/DeepBeliefSDK

We evaluate whether features extracted from the activation of a deep convolutional network trained in a fully supervised fashion on a large, fixed set of object recognition tasks can be re-purposed to novel generic tasks.

DOMAIN ADAPTATION OBJECT RECOGNITION SCENE RECOGNITION TRANSFER LEARNING

OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks

21 Dec 2013soumith/convnet-benchmarks

This integrated framework is the winner of the localization task of the ImageNet Large Scale Visual Recognition Challenge 2013 (ILSVRC2013) and obtained very competitive results for the detection and classifications tasks.

IMAGE CLASSIFICATION OBJECT DETECTION OBJECT RECOGNITION

Some Improvements on Deep Convolutional Neural Network Based Image Classification

19 Dec 2013facebookarchive/fb.resnet.torch

We investigate multiple techniques to improve upon the current state of the art deep convolutional neural network based image classification pipeline.

IMAGE CLASSIFICATION OBJECT RECOGNITION

Cutting the Error by Half: Investigation of Very Deep CNN and Advanced Training Strategies for Document Image Classification

11 Apr 2017microsoft/unilm

We present an exhaustive investigation of recent Deep Learning architectures, algorithms, and strategies for the task of document image classification to finally reduce the error by more than half.

DOCUMENT IMAGE CLASSIFICATION OBJECT RECOGNITION TRANSFER LEARNING