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 921–930 of 2042 papers

Title	Date	Tasks	Status
Open-Ended Fine-Grained 3D Object Categorization by Combining Shape and Texture Features in Multiple Colorspaces	Sep 19, 2020	3D Object RecognitionDescriptive	—Unverified
HR-RCNN: Hierarchical Relational Reasoning for Object Detection	Oct 26, 2021	Graph AttentionInstance Segmentation	—Unverified
Exploit Bounding Box Annotations for Multi-label Object Recognition	Apr 22, 2015	Multi-Label ClassificationObject	—Unverified
Explicitly Modeling Subcortical Vision with a Neuro-Inspired Front-End Improves CNN Robustness	Jun 3, 2025	Data AugmentationObject Recognition	—Unverified
Combining Lexical and Spatial Knowledge to Predict Spatial Relations between Objects in Images	Aug 1, 2016	Object DetectionObject Recognition	—Unverified
A Proper Orthogonal Decomposition approach for parameters reduction of Single Shot Detector networks	Jul 27, 2022	Dimensionality ReductionObject Recognition	—Unverified
Explaining Clinical Decision Support Systems in Medical Imaging using Cycle-Consistent Activation Maximization	Oct 9, 2020	Breast Cancer DetectionDecision Making	—Unverified
Human peripheral blur is optimal for object recognition	Jul 23, 2018	ObjectObject Recognition	—Unverified
Combining Deep Transfer Learning with Signal-image Encoding for Multi-Modal Mental Wellbeing Classification	Nov 20, 2020	Emotion ClassificationGeneral Classification	—Unverified
Explainability Tools Enabling Deep Learning in Future In-Situ Real-Time Planetary Explorations	Jan 15, 2022	Image SegmentationObject 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