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 1776–1800 of 2042 papers

Title	Date	Tasks	Status
Sublinear Partition Estimation	Aug 7, 2015	Language ModelingLanguage Modelling	CodeCode Available
UnSegGNet: Unsupervised Image Segmentation using Graph Neural Networks	May 9, 2024	Image SegmentationObject Recognition	CodeCode Available
Places205-VGGNet Models for Scene Recognition	Aug 7, 2015	Computational EfficiencyGPU	CodeCode Available
Multi-area Target Individual Detection with Free Drawing on Video	Jul 6, 2022	Object Recognition	CodeCode Available
A Framework of Transfer Learning in Object Detection for Embedded Systems	Nov 12, 2018	Hyperparameter OptimizationObject	CodeCode Available
Human Eyes Inspired Recurrent Neural Networks are More Robust Against Adversarial Noises	Jun 15, 2022	Adversarial RobustnessFoveation	CodeCode Available
Point Cloud GAN	Oct 13, 2018	Object Recognition	CodeCode Available
Human-like Clustering with Deep Convolutional Neural Networks	Jun 15, 2017	ClusteringObject Recognition	CodeCode Available
An Analysis of Unsupervised Pre-training in Light of Recent Advances	Dec 20, 2014	Data AugmentationImage Classification	CodeCode Available
Chessboard and chess piece recognition with the support of neural networks	Aug 13, 2017	Object Recognition	CodeCode Available
Human Pose Estimation for Real-World Crowded Scenarios	Jul 16, 2019	Data AugmentationObject Recognition	CodeCode Available
Multi-Label Sentiment Analysis on 100 Languages with Dynamic Weighting for Label Imbalance	Aug 26, 2020	Object RecognitionSentiment Analysis	CodeCode Available
A comparison between humans and AI at recognizing objects in unusual poses	Feb 6, 2024	Object Recognition	CodeCode Available
Disparity Sliding Window: Object Proposals From Disparity Images	May 17, 2018	Objectobject-detection	CodeCode Available
Pointwise Convolutional Neural Networks	Dec 14, 2017	ObjectObject Recognition	CodeCode Available
Multimodal Deep Learning for Robust RGB-D Object Recognition	Jul 24, 2015	Data AugmentationDeep Learning	CodeCode Available
Five Points to Check when Comparing Visual Perception in Humans and Machines	Apr 20, 2020	Decision MakingObject Recognition	CodeCode Available
Multi-path Convolutional Neural Networks for Complex Image Classification	Jun 15, 2015	ClassificationGeneral Classification	CodeCode Available
Foveated Instance Segmentation	Mar 27, 2025	Instance SegmentationObject Recognition	CodeCode Available
Continual Learning in Neural Networks	Oct 7, 2019	Continual LearningObject Recognition	CodeCode Available
Tuned Compositional Feature Replays for Efficient Stream Learning	Apr 6, 2021	Continual LearningImage Classification	CodeCode Available
Discriminative Unsupervised Feature Learning with Convolutional Neural Networks	Dec 1, 2014	General ClassificationImage Classification	CodeCode Available
FoodTracker: A Real-time Food Detection Mobile Application by Deep Convolutional Neural Networks	Sep 13, 2019	NutritionObject Recognition	CodeCode Available
Visual Story Generation Based on Emotion and Keywords	Jan 7, 2023	Image GenerationObject Recognition	CodeCode Available
Improving Out-of-Distribution Detection with Disentangled Foreground and Background Features	Mar 15, 2023	DisentanglementObject Recognition	CodeCode Available

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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