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 551–560 of 2042 papers

Title	Date	Tasks	Status	Hype
Label Efficient Regularization and Propagation for Graph Node Classification	Apr 19, 2022	AttributeBenchmarking	—Unverified	0
Sensitivity of sparse codes to image distortions	Apr 15, 2022	Object RecognitionSensitivity	—Unverified	0
Joint Distribution Matters: Deep Brownian Distance Covariance for Few-Shot Classification	Apr 9, 2022	Classificationdomain classification	CodeCode Available	1
Hybrid Predictive Coding: Inferring, Fast and Slow	Apr 5, 2022	Bayesian InferenceObject Recognition	—Unverified	0
Exploiting Temporal Relations on Radar Perception for Autonomous Driving	Apr 3, 2022	2D Object DetectionAutonomous Driving	—Unverified	0
Neurosymbolic hybrid approach to driver collision warning	Mar 28, 2022	Autonomous DrivingDeep Learning	—Unverified	0
Salt Detection Using Segmentation of Seismic Image	Mar 25, 2022	Object RecognitionSeismic Imaging	—Unverified	0
Ev-TTA: Test-Time Adaptation for Event-Based Object Recognition	Mar 23, 2022	Event-based visionObject Recognition	CodeCode Available	1
Visuo-Haptic Object Perception for Robots: An Overview	Mar 22, 2022	ArticlesObject	—Unverified	0
A Real-time Junk Food Recognition System based on Machine Learning	Mar 22, 2022	BIG-bench Machine LearningFood 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