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 1461–1470 of 2042 papers

Title	Date	Tasks	Status
MMSS: Multi-Modal Sharable and Specific Feature Learning for RGB-D Object Recognition	Dec 1, 2015	ObjectObject Recognition	—Unverified
Modality and Component Aware Feature Fusion For RGB-D Scene Classification	Jun 1, 2016	General ClassificationObject Recognition	—Unverified
Model alignment using inter-modal bridges	May 18, 2025	Image Generationmodel	—Unverified
Model-based active learning to detect isometric deformable objects in the wild with deep architectures	Jun 7, 2018	Active LearningObject	—Unverified
Model compression as constrained optimization, with application to neural nets. Part I: general framework	Jul 5, 2017	Model CompressionObject Recognition	—Unverified
Modeling biological face recognition with deep convolutional neural networks	Aug 13, 2022	Face DetectionFace Identification	—Unverified
Modeling Human Development: Effects of Blurred Vision on Category Learning in CNNs	Jan 1, 2021	ClassificationGeneral Classification	—Unverified
Modeling infant object perception as program induction	Aug 28, 2023	AttributeInductive Learning	—Unverified
Modeling Object Recognition in Newborn Chicks using Deep Neural Networks	Jun 14, 2021	ObjectObject Recognition	—Unverified
Modeling the Contribution of Central Versus Peripheral Vision in Scene, Object, and Face Recognition	Apr 25, 2016	Face RecognitionObject 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