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 251–260 of 2042 papers

Title	Date	Tasks	Status
Basic Level Categorization Facilitates Visual Object Recognition	Nov 12, 2015	ObjectObject Categorization	—Unverified
An Adaptive Descriptor Design for Object Recognition in the Wild	May 1, 2013	Domain AdaptationObject	—Unverified
Belief Tree Search for Active Object Recognition	Aug 13, 2017	ObjectObject Recognition	—Unverified
Benchmarking Out-of-Distribution Generalization Capabilities of DNN-based Encoding Models for the Ventral Visual Cortex	Jun 16, 2024	BenchmarkingObject Recognition	—Unverified
ATZSL: Defensive Zero-Shot Recognition in the Presence of Adversaries	Oct 24, 2019	Image CaptioningObject Recognition	—Unverified
A Machine Learning Framework for Distributed Functional Compression over Wireless Channels in IoT	Jan 24, 2022	Autonomous DrivingBIG-bench Machine Learning	—Unverified
A Bayesian Framework for Active Tactile Object Recognition, Pose Estimation and Shape Transfer Learning	Sep 10, 2024	Active LearningObject	—Unverified
Attribute-Based Classification for Zero-Shot Visual Object Categorization	Jul 30, 2013	AttributeClassification	—Unverified
A low-power end-to-end hybrid neuromorphic framework for surveillance applications	Oct 22, 2019	ClassificationGeneral Classification	—Unverified
AttoNets: Compact and Efficient Deep Neural Networks for the Edge via Human-Machine Collaborative Design	Mar 18, 2019	object-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