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 1951–1960 of 2042 papers

Title	Date	Tasks	Status
Learned-Norm Pooling for Deep Feedforward and Recurrent Neural Networks	Nov 7, 2013	Object Recognition	—Unverified
Object Recognition System Design in Computer Vision: a Universal Approach	Oct 27, 2013	General Classificationobject-detection	—Unverified
DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition	Oct 6, 2013	ClusteringDomain Adaptation	CodeCode Available
Image Description using Visual Dependency Representations	Oct 1, 2013	Image DescriptionImage Retrieval	—Unverified
Surface Registration Using Genetic Algorithm in Reduced Search Space	Oct 1, 2013	Object Recognitionparameter estimation	—Unverified
Suspicious Object Recognition Method in Video Stream Based on Visual Attention	Aug 23, 2013	ObjectObject Recognition	—Unverified
MonoStream: A Minimal-Hardware High Accuracy Device-free WLAN Localization System	Aug 4, 2013	Object RecognitionVocal Bursts Intensity Prediction	—Unverified
VSEM: An open library for visual semantics representation	Aug 1, 2013	Image ClassificationImage Retrieval	—Unverified
Visual Features for Linguists: Basic image analysis techniques for multimodally-curious NLPers	Aug 1, 2013	Emotion RecognitionObject Recognition	—Unverified
Domain-invariant Face Recognition using Learned Low-rank Transformation	Aug 1, 2013	Face RecognitionObject 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