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 271–280 of 2042 papers

Title	Date	Tasks	Status
A temporal neural network model for object recognition using a biologically plausible decision making layer	Jun 25, 2018	Decision MakingObject Recognition	—Unverified
`Lighter' Can Still Be Dark: Modeling Comparative Color Descriptions	Jul 1, 2018	Object Recognition	—Unverified
A Systematic Study on Object Recognition Using Millimeter-wave Radar	May 3, 2023	ObjectObject Localization	—Unverified
A Survey on Recent Advances of Computer Vision Algorithms for Egocentric Video	Jan 12, 2015	Action DetectionActivity Detection	—Unverified
Adaptive Color Attributes for Real-Time Visual Tracking	Jun 1, 2014	AttributeImage Description	—Unverified
AAD: Adaptive Anomaly Detection through traffic surveillance videos	Aug 29, 2018	Action DetectionActivity Detection	—Unverified
Capturing the objects of vision with neural networks	Sep 7, 2021	ObjectObject Recognition	—Unverified
Catastrophic Child's Play: Easy to Perform, Hard to Defend Adversarial Attacks	Jun 1, 2019	Data AugmentationObject	—Unverified
CausalX: Causal Explanations and Block Multilinear Factor Analysis	Feb 25, 2021	Computational Efficiencycounterfactual	—Unverified
A Survey of Task-Based Machine Learning Content Extraction Services for VIDINT	Jul 9, 2022	BIG-bench Machine LearningMachine Translation	—Unverified

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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