Object Recognition

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 )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1526–1550 of 2042 papers

Title	Date	Tasks	Status	Hype
Learning Hard Alignments with Variational Inference	May 16, 2017	Hard AttentionImage Captioning	—Unverified	0
View-Invariant Template Matching Using Homography Constraints	May 12, 2017	ObjectObject Recognition	—Unverified	0
Using Satellite Imagery for Good: Detecting Communities in Desert and Mapping Vaccination Activities	May 12, 2017	Object Recognition	—Unverified	0
Gabor Filter Assisted Energy Efficient Fast Learning Convolutional Neural Networks	May 12, 2017	Face DetectionObject Recognition	—Unverified	0
Reducing Bias in Production Speech Models	May 11, 2017	Object Recognition	—Unverified	0
Collaborative Descriptors: Convolutional Maps for Preprocessing	May 10, 2017	Object Recognition	—Unverified	0
CORe50: a New Dataset and Benchmark for Continuous Object Recognition	May 9, 2017	Continuous Object RecognitionLifelong learning	CodeCode Available	0
Bridging between Computer and Robot Vision through Data Augmentation: a Case Study on Object Recognition	May 5, 2017	Data AugmentationObject	—Unverified	0
DeepCorrect: Correcting DNN models against Image Distortions	May 5, 2017	ClassificationGeneral Classification	CodeCode Available	0
From Zero-shot Learning to Conventional Supervised Classification: Unseen Visual Data Synthesis	May 4, 2017	General ClassificationObject Recognition	—Unverified	0
Recurrent Soft Attention Model for Common Object Recognition	May 4, 2017	modelObject	CodeCode Available	0
Inception Recurrent Convolutional Neural Network for Object Recognition	Apr 25, 2017	ObjectObject Recognition	CodeCode Available	0
Towards Instance Segmentation with Object Priority: Prominent Object Detection and Recognition	Apr 24, 2017	Instance SegmentationObject	—Unverified	0
Residual Attention Network for Image Classification	Apr 23, 2017	General Classificationimage-classification	CodeCode Available	0
Track Everything: Limiting Prior Knowledge in Online Multi-Object Recognition	Apr 21, 2017	General ClassificationMulti-Object Tracking	—Unverified	0
Invariant recognition drives neural representations of action sequences	Apr 20, 2017	Action RecognitionObject Recognition	—Unverified	0
BranchConnect: Large-Scale Visual Recognition with Learned Branch Connections	Apr 20, 2017	Image CategorizationObject Recognition	—Unverified	0
Ranking to Learn: Feature Ranking and Selection via Eigenvector Centrality	Apr 18, 2017	feature selectionObject Recognition	—Unverified	0
Cutting the Error by Half: Investigation of Very Deep CNN and Advanced Training Strategies for Document Image Classification	Apr 11, 2017	document-image-classificationDocument Image Classification	CodeCode Available	0
Deep Affordance-grounded Sensorimotor Object Recognition	Apr 10, 2017	ObjectObject Recognition	—Unverified	0
Generate To Adapt: Aligning Domains using Generative Adversarial Networks	Apr 6, 2017	Domain AdaptationGenerative Adversarial Network	CodeCode Available	0
Pragmatic descriptions of perceptual stimuli	Apr 1, 2017	Image DescriptionObject Recognition	—Unverified	0
Multiple Instance Detection Network with Online Instance Classifier Refinement	Apr 1, 2017	Multiple Instance LearningObject	CodeCode Available	1
Learning with Privileged Information for Multi-Label Classification	Mar 29, 2017	Action Unit DetectionClassification	—Unverified	0
Object categorization in finer levels requires higher spatial frequencies, and therefore takes longer	Mar 29, 2017	Object CategorizationObject Recognition	—Unverified	0

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All datasets shape bias CIFAR10-DVS N-Caltech 101 ObjectNet (All classes)ObjectNet (ImageNet classes)ObjectNet (ImageNet classes, trained on ImageNet)DVS128 Gesture MECCANO N-CARS

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	Imagen	shape bias	98.7	—	Unverified
2	Stable Diffusion	shape bias	92.7	—	Unverified
3	Parti	shape bias	91.7	—	Unverified
4	ViT-22B-384	shape bias	86.4	—	Unverified
5	ViT-22B-560	shape bias	83.8	—	Unverified
6	CLIP (ViT-B)	shape bias	79.9	—	Unverified
7	ViT-22B-224	shape bias	78	—	Unverified
8	ResNet-50 (L2 eps 5.0 adv trained)	shape bias	69.5	—	Unverified
9	ResNet-50 (with strong augmentations)	shape bias	62.2	—	Unverified
10	SWSL (ResNeXt-101)	shape bias	49.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Spike-VGG11	Accuracy (% )	85.55	—	Unverified
2	SSNN	Accuracy (% )	78.57	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Spike-VGG11	Accuracy (% )	85.62	—	Unverified
2	SSNN	Accuracy (% )	79.25	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ObjectNet-Baseline	Top 5 Accuracy	18.75	—	Unverified
2	yun	Top 5 Accuracy	14.75	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ObjectNet-Baseline	Top 5 Accuracy	52.24	—	Unverified
2	DY	Top 5 Accuracy	0.08	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ObjectNet-Baseline	Top 5 Accuracy	52.24	—	Unverified
2	AJ2021	Top 5 Accuracy	27.68	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SSNN	Accuracy (% )	94.91	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Faster-RCNN	mAP	30.39	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Spike-VGG11	Accuracy (% )	96	—	Unverified