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 1981–1990 of 2042 papers

Title	Date	Tasks	Status
Learning to Detect Important People in Unlabelled Images for Semi-supervised Important People Detection	Apr 16, 2020	Object RecognitionPseudo Label	CodeCode Available
Learning to Find Common Objects Across Few Image Collections	Apr 29, 2019	Few-Shot LearningObject	CodeCode Available
Comparative Study Between Distance Measures On Supervised Optimum-Path Forest Classification	Feb 8, 2022	Anomaly DetectionBenchmarking	CodeCode Available
Opening Deep Neural Networks with Generative Models	May 20, 2021	image-classificationImage Classification	CodeCode Available
OpenLORIS-Object: A Robotic Vision Dataset and Benchmark for Lifelong Deep Learning	Nov 15, 2019	Lifelong learningObject	CodeCode Available
OpenNav: Efficient Open Vocabulary 3D Object Detection for Smart Wheelchair Navigation	Aug 25, 2024	3D Object DetectionNavigate	CodeCode Available
Open-Set 3D Semantic Instance Maps for Vision Language Navigation -- O3D-SIM	Apr 27, 2024	Image SegmentationNavigate	CodeCode Available
Are Vision Transformers More Data Hungry Than Newborn Visual Systems?	Dec 5, 2023	ObjectObject Recognition	CodeCode Available
Deep Learning with Nonparametric Clustering	Jan 13, 2015	ClusteringDeep Learning	CodeCode Available
Theano-based Large-Scale Visual Recognition with Multiple GPUs	Dec 7, 2014	GPUObject Recognition	CodeCode Available

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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