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 51–60 of 2042 papers

Title	Date	Tasks	Status	Hype
Benchmarking Multimodal Mathematical Reasoning with Explicit Visual Dependency	Apr 24, 2025	BenchmarkingMath	CodeCode Available	1
Densely Connected Convolutional Networks	Aug 25, 2016	Breast Tumour ClassificationClassification	CodeCode Available	1
Equalization Loss for Long-Tailed Object Recognition	Mar 11, 2020	Long-tail LearningObject	CodeCode Available	1
Describing Textures in the Wild	Nov 14, 2013	Material RecognitionObject Recognition	CodeCode Available	1
Distributed Deep Neural Networks over the Cloud, the Edge and End Devices	Sep 6, 2017	Distributed ComputingObject Recognition	CodeCode Available	1
Divergences in Color Perception between Deep Neural Networks and Humans	Sep 11, 2023	image-classificationImage Classification	CodeCode Available	1
DOCTOR: A Simple Method for Detecting Misclassification Errors	Jun 4, 2021	Object RecognitionSentiment Analysis	CodeCode Available	1
Domain Generalization for Object Recognition with Multi-task Autoencoders	Aug 31, 2015	DenoisingDomain Generalization	CodeCode Available	1
Dynamic Few-Shot Visual Learning without Forgetting	Apr 25, 2018	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1
CSIM: A Copula-based similarity index sensitive to local changes for Image quality assessment	Oct 2, 2024	AstronomyImage Quality Assessment	CodeCode Available	1

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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