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 1521–1530 of 2042 papers

Title	Date	Tasks	Status
Noise-Adaptive Intelligent Programmable Meta-Imager	Aug 22, 2022	Earth ObservationObject Recognition	—Unverified
Non-iterative recomputation of dense layers for performance improvement of DCNN	Sep 14, 2018	Object Recognition	—Unverified
Non-parametric Image Registration of Airborne LiDAR, Hyperspectral and Photographic Imagery of Forests	Jul 28, 2014	Image RegistrationObject Recognition	—Unverified
Number detectors spontaneously emerge in a deep neural network designed for visual object recognition	May 8, 2019	ObjectObject Recognition	—Unverified
Object and Text-guided Semantics for CNN-based Activity Recognition	May 4, 2018	Activity RecognitionHuman Activity Recognition	—Unverified
Object-aware Feature Aggregation for Video Object Detection	Oct 23, 2020	Objectobject-detection	—Unverified
Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature Sparsification	Dec 1, 2010	General ClassificationObject	—Unverified
Object categorization in finer levels requires higher spatial frequencies, and therefore takes longer	Mar 29, 2017	Object CategorizationObject Recognition	—Unverified
Object-Centric World Model for Language-Guided Manipulation	Mar 8, 2025	Autonomous Drivingmodel	—Unverified
Object classification in images of Neoclassical furniture using Deep Learning	Mar 7, 2017	ClassificationDeep Learning	—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