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 711–720 of 2042 papers

Title	Date	Tasks	Status
300 GHz Radar Object Recognition based on Deep Neural Networks and Transfer Learning	Dec 6, 2019	ObjectObject Recognition	—Unverified
Face Identification with Second-Order Pooling	Jun 26, 2014	Face IdentificationFace Recognition	—Unverified
Distributional Instance Segmentation: Modeling Uncertainty and High Confidence Predictions with Latent-MaskRCNN	May 3, 2023	Instance SegmentationObject Recognition	—Unverified
EventDance++: Language-guided Unsupervised Source-free Cross-modal Adaptation for Event-based Object Recognition	Sep 19, 2024	Object Recognition	—Unverified
EventDance: Unsupervised Source-free Cross-modal Adaptation for Event-based Object Recognition	Mar 21, 2024	Object RecognitionTransfer Learning	—Unverified
EventF2S: Asynchronous and Sparse Spiking AER Framework using Neuromorphic-Friendly Algorithm	Jan 28, 2024	DenoisingObject Recognition	—Unverified
BranchConnect: Large-Scale Visual Recognition with Learned Branch Connections	Apr 20, 2017	Image CategorizationObject Recognition	—Unverified
EV-Flying: an Event-based Dataset for In-The-Wild Recognition of Flying Objects	Jun 4, 2025	Event-based visionObject Recognition	—Unverified
Distributed Coding of Multiview Sparse Sources with Joint Recovery	Jul 18, 2016	compressed sensingObject Recognition	—Unverified
A Neuro-AI Interface: Learning DNNs from the Human Brain	May 28, 2019	Object RecognitionOpen-Ended Question Answering	—Unverified

Show:10 25 50

← PrevPage 72 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