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 1021–1030 of 2042 papers

Title	Date	Tasks	Status
Optimistic and Pessimistic Neural Networks for Scene and Object Recognition	Sep 26, 2016	AttributeObject Recognition	—Unverified
Optimizing Sparse Convolution on GPUs with CUDA for 3D Point Cloud Processing in Embedded Systems	Feb 12, 2024	Object Recognition	—Unverified
Optimized CNNs for Rapid 3D Point Cloud Object Recognition	Dec 3, 2024	Computational Efficiencyobject-detection	—Unverified
Optimizing Multi-Domain Performance with Active Learning-based Improvement Strategies	Apr 13, 2023	Active Learningimage-classification	—Unverified
ORCEA: Object Recognition by Continuous Evidence Assimilation	May 11, 2021	ObjectObject Recognition	—Unverified
Orientation-boosted Voxel Nets for 3D Object Recognition	Apr 12, 2016	3D Object RecognitionClassification	—Unverified
Oriented Feature Alignment for Fine-grained Object Recognition in High-Resolution Satellite Imagery	Oct 13, 2021	Objectobject-detection	—Unverified
Origami: A 803 GOp/s/W Convolutional Network Accelerator	Dec 14, 2015	Action RecognitionObject Recognition	—Unverified
OSMa-Bench: Evaluating Open Semantic Mapping Under Varying Lighting Conditions	Mar 13, 2025	Object RecognitionSemantic Segmentation	—Unverified
OTAdapt: Optimal Transport-based Approach For Unsupervised Domain Adaptation	May 22, 2022	Domain AdaptationObject Recognition	—Unverified

Show:10 25 50

← PrevPage 103 of 205Next →

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