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 1771–1780 of 2042 papers

Title	Date	Tasks	Status
Complete End-To-End Low Cost Solution To a 3D Scanning System with Integrated Turntable	Sep 3, 2017	3D ReconstructionObject Recognition	—Unverified
Complex-valued Iris Recognition Network	Nov 23, 2020	Iris RecognitionObject Recognition	—Unverified
Compositional Convolutional Neural Networks: A Robust and Interpretable Model for Object Recognition under Occlusion	Jun 28, 2020	image-classificationImage Classification	—Unverified
Compositional Embeddings for Multi-Label One-Shot Learning	Feb 11, 2020	Object DetectionObject Recognition	—Unverified
Compositional Hierarchical Tensor Factorization: Representing Hierarchical Intrinsic and Extrinsic Causal Factors	Nov 11, 2019	Face RecognitionObject	—Unverified
Compressing Deep Convolutional Networks using Vector Quantization	Dec 18, 2014	ClassificationClustering	—Unverified
Compression of Deep Neural Networks on the Fly	Sep 29, 2015	Object RecognitionQuantization	—Unverified
Computer vision and machine learning for medical image analysis: recent advances, challenges, and way forward	Mar 21, 2022	image-classificationImage Classification	—Unverified
Connecting metrics for shape-texture knowledge in computer vision	Jan 25, 2023	image-classificationImage Classification	—Unverified
Consistency of Silhouettes and Their Duals	Jun 1, 2016	Camera CalibrationObject	—Unverified

Show:10 25 50

← PrevPage 178 of 205Next →

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