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 1791–1800 of 2042 papers

Title	Date	Tasks	Status
Multiscale Adaptive Representation of Signals: I. The Basic Framework	Jul 17, 2015	Computational EfficiencyDenoising	—Unverified
Deep Learning and Music Adversaries	Jul 16, 2015	Deep LearningObject Recognition	—Unverified
Robot In a Room: Toward Perfect Object Recognition in Closed Environments	Jul 9, 2015	ObjectObject Recognition	—Unverified
Linking Entities Across Images and Text	Jul 1, 2015	Entity LinkingImage Retrieval	—Unverified
Describing Images using Inferred Visual Dependency Representations	Jul 1, 2015	Object RecognitionText Generation	—Unverified
Occlusion Coherence: Detecting and Localizing Occluded Faces	Jun 28, 2015	Face DetectionObject Recognition	CodeCode Available
Natural Scene Recognition Based on Superpixels and Deep Boltzmann Machines	Jun 24, 2015	ClusteringHandwritten Digit Recognition	—Unverified
A Novel Feature Extraction Method for Scene Recognition Based on Centered Convolutional Restricted Boltzmann Machines	Jun 24, 2015	Object RecognitionScene Recognition	—Unverified
A Discriminative Representation of Convolutional Features for Indoor Scene Recognition	Jun 17, 2015	ObjectObject Recognition	—Unverified
Multi-path Convolutional Neural Networks for Complex Image Classification	Jun 15, 2015	ClassificationGeneral Classification	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