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 1971–1980 of 2042 papers

Title	Date	Tasks	Status
Fully-Connected CRFs with Non-Parametric Pairwise Potential	Jun 1, 2013	DenoisingDensity Estimation	—Unverified
Learning and Calibrating Per-Location Classifiers for Visual Place Recognition	Jun 1, 2013	Object RecognitionTwo-sample testing	—Unverified
Kernel Null Space Methods for Novelty Detection	Jun 1, 2013	Density EstimationNovelty Detection	—Unverified
Perceptual Organization and Recognition of Indoor Scenes from RGB-D Images	Jun 1, 2013	Boundary DetectionContour Detection	—Unverified
Efficient 2D-to-3D Correspondence Filtering for Scalable 3D Object Recognition	Jun 1, 2013	3D Object RecognitionCPU	—Unverified
Mesh Based Semantic Modelling for Indoor and Outdoor Scenes	Jun 1, 2013	ObjectObject Recognition	—Unverified
Understanding Bayesian Rooms Using Composite 3D Object Models	Jun 1, 2013	ObjectObject Recognition	—Unverified
SCaLE: Supervised and Cascaded Laplacian Eigenmaps for Visual Object Recognition Based on Nearest Neighbors	Jun 1, 2013	Object Recognition	—Unverified
Learning Collections of Part Models for Object Recognition	Jun 1, 2013	ObjectObject Recognition	—Unverified
Scene Parsing by Integrating Function, Geometry and Appearance Models	Jun 1, 2013	ObjectObject Recognition	—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