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 731–740 of 2042 papers

Title	Date	Tasks	Status
Explicitly Modeling Subcortical Vision with a Neuro-Inspired Front-End Improves CNN Robustness	Jun 3, 2025	Data AugmentationObject Recognition	—Unverified
Exploit Bounding Box Annotations for Multi-label Object Recognition	Apr 22, 2015	Multi-Label ClassificationObject	—Unverified
Fast Object Detection with a Machine Learning Edge Device	Oct 5, 2024	Autonomous NavigationCPU	—Unverified
Exploiting an Oracle that Reports AUC Scores in Machine Learning Contests	Jun 3, 2015	BIG-bench Machine LearningBinary Classification	—Unverified
A Neural Spiking Approach Compared to Deep Feedforward Networks on Stepwise Pixel Erasement	Dec 6, 2019	ClassificationGeneral Classification	—Unverified
Exploiting Spatio-Temporal Structure with Recurrent Winner-Take-All Networks	Oct 31, 2016	AllObject Recognition	—Unverified
BrainSlug: Transparent Acceleration of Deep Learning Through Depth-First Parallelism	Apr 23, 2018	Deep LearningMachine Translation	—Unverified
Exploiting the ConvLSTM: Human Action Recognition using Raw Depth Video-Based Recurrent Neural Networks	Jun 13, 2020	Action RecognitionObject Recognition	—Unverified
Fast Fourier Transformation for Optimizing Convolutional Neural Networks in Object Recognition	Oct 8, 2020	Object Recognition	—Unverified
Disentangling Properties of Contrastive Methods	Sep 29, 2021	DisentanglementObject 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