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 691–700 of 2042 papers

Title	Date	Tasks	Status	Hype
Prediction Surface Uncertainty Quantification in Object Detection Models for Autonomous Driving	Jul 11, 2021	Autonomous DrivingDecision Making	CodeCode Available	0
On the Challenges of Open World Recognitionunder Shifting Visual Domains	Jul 9, 2021	Domain GeneralizationObject Recognition	CodeCode Available	1
Mind Your Outliers! Investigating the Negative Impact of Outliers on Active Learning for Visual Question Answering	Jul 6, 2021	Active LearningObject Recognition	CodeCode Available	1
MixStyle Neural Networks for Domain Generalization and Adaptation	Jul 5, 2021	Data AugmentationDomain Adaptation	—Unverified	0
Hebbian learning with gradients: Hebbian convolutional neural networks with modern deep learning frameworks	Jul 4, 2021	Deep LearningObject Recognition	CodeCode Available	1
Parasitic Egg Detection and Classification in Low-cost Microscopic Images using Transfer Learning	Jul 2, 2021	ClassificationObject Recognition	—Unverified	0
Understanding Adversarial Examples Through Deep Neural Network's Response Surface and Uncertainty Regions	Jun 30, 2021	Classificationimage-classification	—Unverified	0
In-distribution adversarial attacks on object recognition models using gradient-free search	Jun 30, 2021	Adversarial AttackAttribute	CodeCode Available	0
PatentNet: A Large-Scale Incomplete Multiview, Multimodal, Multilabel Industrial Goods Image Database	Jun 23, 2021	BenchmarkingClustering	—Unverified	0
SISA: Securing Images by Selective Alteration	Jun 20, 2021	Object Recognition	—Unverified	0

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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