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 791–800 of 2042 papers

Title	Date	Tasks	Status
Saliency for free: Saliency prediction as a side-effect of object recognition	Jul 20, 2021	Object RecognitionSaliency Prediction	—Unverified
Spectral Processing and Optimization of Static and Dynamic 3D Geometries	Jul 15, 2021	3D geometry3D Object Recognition	—Unverified
Applications of knowledge graphs for food science and industry	Jul 13, 2021	Data Visualizationgraph construction	—Unverified
The Foes of Neural Network's Data Efficiency Among Unnecessary Input Dimensions	Jul 13, 2021	Object Recognition	—Unverified
Prediction Surface Uncertainty Quantification in Object Detection Models for Autonomous Driving	Jul 11, 2021	Autonomous DrivingDecision Making	CodeCode Available
MixStyle Neural Networks for Domain Generalization and Adaptation	Jul 5, 2021	Data AugmentationDomain Adaptation	—Unverified
Parasitic Egg Detection and Classification in Low-cost Microscopic Images using Transfer Learning	Jul 2, 2021	ClassificationObject Recognition	—Unverified
Understanding Adversarial Examples Through Deep Neural Network's Response Surface and Uncertainty Regions	Jun 30, 2021	Classificationimage-classification	—Unverified
In-distribution adversarial attacks on object recognition models using gradient-free search	Jun 30, 2021	Adversarial AttackAttribute	CodeCode Available
PatentNet: A Large-Scale Incomplete Multiview, Multimodal, Multilabel Industrial Goods Image Database	Jun 23, 2021	BenchmarkingClustering	—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