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 901–910 of 2042 papers

Title	Date	Tasks	Status
mDALU: Multi-Source Domain Adaptation and Label Unification with Partial Datasets	Dec 15, 2020	3D Semantic SegmentationDomain Adaptation	—Unverified
Deep Learning for Material recognition: most recent advances and open challenges	Dec 14, 2020	Deep LearningMaterial Recognition	—Unverified
Assessing The Importance Of Colours For CNNs In Object Recognition	Dec 12, 2020	Fine-Grained Image ClassificationGeneral Classification	—Unverified
Interpretable Graph Capsule Networks for Object Recognition	Dec 3, 2020	Adversarial RobustnessObject	—Unverified
Unsupervised Part Discovery via Feature Alignment	Dec 1, 2020	ObjectObject Recognition	—Unverified
Towards real-time object recognition and pose estimation in point clouds	Nov 27, 2020	Objectobject-detection	—Unverified
Adversarial Attack on Facial Recognition using Visible Light	Nov 25, 2020	Adversarial Attackobject-detection	—Unverified
Insights From A Large-Scale Database of Material Depictions In Paintings	Nov 24, 2020	Domain AdaptationInteractive Segmentation	—Unverified
Complex-valued Iris Recognition Network	Nov 23, 2020	Iris RecognitionObject Recognition	—Unverified
Industrial object, machine part and defect recognition towards fully automated industrial monitoring employing deep learning. The case of multilevel VGG19	Nov 23, 2020	Defect Detectionobject-detection	—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