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 381–390 of 2042 papers

Title	Date	Tasks	Status
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
Convolutional Spike Timing Dependent Plasticity based Feature Learning in Spiking Neural Networks	Mar 10, 2017	Object Recognition	—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
CogNav: Cognitive Process Modeling for Object Goal Navigation with LLMs	Dec 11, 2024	Large Language ModelObject	—Unverified
Applications of Probabilistic Programming (Master's thesis, 2015)	May 31, 2016	Object RecognitionProbabilistic Programming	—Unverified
Connecting metrics for shape-texture knowledge in computer vision	Jan 25, 2023	image-classificationImage Classification	—Unverified
A Comprehensive Study of ImageNet Pre-Training for Historical Document Image Analysis	May 22, 2019	General ClassificationImage Classification	—Unverified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