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 881–890 of 2042 papers

Title	Date	Tasks	Status
Hand-Priming in Object Localization for Assistive Egocentric Vision	Feb 28, 2020	Hand SegmentationMulti-Task Learning	—Unverified
Crowdsourcing in Computer Vision	Nov 7, 2016	Object Recognition	—Unverified
An Efficient Semi-Automated Scheme for Infrastructure LiDAR Annotation	Jan 25, 2023	Autonomous DrivingMulti-Object Tracking	—Unverified
Hardening RGB-D Object Recognition Systems against Adversarial Patch Attacks	Sep 13, 2023	Object Recognition	—Unverified
How Deep is the Feature Analysis underlying Rapid Visual Categorization?	Jun 3, 2016	Object Recognition	—Unverified
Hardware Implementation of Hyperbolic Tangent Function using Catmull-Rom Spline Interpolation	Jul 13, 2020	Object Recognitionspeech-recognition	—Unverified
How Small is Big Enough? Open Labeled Datasets and the Development of Deep Learning	Aug 19, 2024	Deep LearningObject Recognition	—Unverified
CURL: Co-trained Unsupervised Representation Learning for Image Classification	May 29, 2015	ClassificationGeneral Classification	—Unverified
HD-CNN: Hierarchical Deep Convolutional Neural Networks for Large Scale Visual Recognition	Dec 1, 2015	image-classificationImage Classification	—Unverified
Human-like general language processing	May 19, 2020	Object RecognitionSentence	—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