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 1111–1120 of 2042 papers

Title	Date	Tasks	Status
Using Motion and Internal Supervision in Object Recognition	Dec 13, 2018	Motion SegmentationObject	—Unverified
Using Satellite Imagery for Good: Detecting Communities in Desert and Mapping Vaccination Activities	May 12, 2017	Object Recognition	—Unverified
Using Spatial Pooler of Hierarchical Temporal Memory to classify noisy videos with predefined complexity	Sep 10, 2016	Object Recognition	—Unverified
Using Web Co-occurrence Statistics for Improving Image Categorization	Dec 19, 2013	Common Sense ReasoningImage Categorization	—Unverified
Utility-Oriented Underwater Image Quality Assessment Based on Transfer Learning	May 7, 2022	Fish DetectionImage Quality Assessment	—Unverified
UWN: A Large Multilingual Lexical Knowledge Base	Jul 1, 2012	Information RetrievalLink Prediction	—Unverified
UW-NET: AN INCEPTION-ATTENTION NETWORK FOR UNDERWATER IMAGE CLASSIFICATION	Jan 1, 2020	ClassificationGeneral Classification	—Unverified
V1Net: A computational model of cortical horizontal connections	Sep 25, 2019	Boundary Detectionmodel	—Unverified
V^2R-Bench: Holistically Evaluating LVLM Robustness to Fundamental Visual Variations	Apr 23, 2025	Dataset GenerationObject Recognition	—Unverified
V2X Cooperative Perception for Autonomous Driving: Recent Advances and Challenges	Oct 5, 2023	Autonomous DrivingAutonomous Vehicles	—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