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 41–50 of 2042 papers

Title	Date	Tasks	Status	Hype	Score
Deep Subdomain Adaptation Network for Image Classification	Jun 17, 2021	ClassificationDomain Adaptation	CodeCode Available	1	5
DesCo: Learning Object Recognition with Rich Language Descriptions	Jun 24, 2023	Language ModelingLanguage Modelling	CodeCode Available	1	5
Describing Textures in the Wild	Nov 14, 2013	Material RecognitionObject Recognition	CodeCode Available	1	5
Do Adversarially Robust ImageNet Models Transfer Better?	Jul 16, 2020	Object RecognitionTransfer Learning	CodeCode Available	1	5
DaWin: Training-free Dynamic Weight Interpolation for Robust Adaptation	Oct 3, 2024	Multi-Task LearningObject Recognition	CodeCode Available	1	5
Debiased Self-Training for Semi-Supervised Learning	Feb 15, 2022	Object RecognitionScene Classification	CodeCode Available	1	5
Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning	May 25, 2016	Object RecognitionVideo Prediction	CodeCode Available	1	5
DeepScores -- A Dataset for Segmentation, Detection and Classification of Tiny Objects	Mar 27, 2018	General ClassificationObject	CodeCode Available	1	5
3D ShapeNets: A Deep Representation for Volumetric Shapes	Jun 22, 2014	3D Point Cloud Classification3D Shape Representation	CodeCode Available	1	5
CSIM: A Copula-based similarity index sensitive to local changes for Image quality assessment	Oct 2, 2024	AstronomyImage Quality Assessment	CodeCode Available	1	5

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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