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	Hype
Unsupervised Cross-Domain Recognition by Identifying Compact Joint Subspaces	Sep 5, 2015	Domain AdaptationObject Recognition	—Unverified	0
Object Recognition from Short Videos for Robotic Perception	Sep 4, 2015	ObjectObject Recognition	—Unverified	0
Visual Classifier Prediction by Distributional Semantic Embedding of Text Descriptions	Sep 1, 2015	Domain AdaptationImage Captioning	—Unverified	0
Generating Image Descriptions with Gold Standard Visual Inputs: Motivation, Evaluation and Baselines	Sep 1, 2015	Image RetrievalObject Recognition	—Unverified	0
From the Virtual to the RealWorld: Referring to Objects in Real-World Spatial Scenes	Sep 1, 2015	Object RecognitionText Generation	—Unverified	0
Domain Generalization for Object Recognition with Multi-task Autoencoders	Aug 31, 2015	DenoisingDomain Generalization	CodeCode Available	1
Partitioning Large Scale Deep Belief Networks Using Dropout	Aug 28, 2015	BIG-bench Machine LearningGPU	—Unverified	0
Deep Networks Can Resemble Human Feed-forward Vision in Invariant Object Recognition	Aug 17, 2015	Object Recognition	—Unverified	0
Sublinear Partition Estimation	Aug 7, 2015	Language ModelingLanguage Modelling	CodeCode Available	0
Places205-VGGNet Models for Scene Recognition	Aug 7, 2015	Computational EfficiencyGPU	CodeCode Available	0
HFirst: A Temporal Approach to Object Recognition	Aug 5, 2015	ObjectObject Recognition	—Unverified	0
Deep supervised learning for hyperspectral data classification through convolutional neural networks	Jul 26, 2015	ClassificationFew-Shot Image Classification	CodeCode Available	0
Thinning Algorithm Using Hypergraph Based Morphological Operators	Jul 25, 2015	Object Recognition	—Unverified	0
Multimodal Deep Learning for Robust RGB-D Object Recognition	Jul 24, 2015	Data AugmentationDeep Learning	CodeCode Available	0
Fourier descriptors based on the structure of the human primary visual cortex with applications to object recognition	Jul 23, 2015	Object RecognitionTranslation	—Unverified	0
Multiscale Adaptive Representation of Signals: I. The Basic Framework	Jul 17, 2015	Computational EfficiencyDenoising	—Unverified	0
Deep Learning and Music Adversaries	Jul 16, 2015	Deep LearningObject Recognition	—Unverified	0
Robot In a Room: Toward Perfect Object Recognition in Closed Environments	Jul 9, 2015	ObjectObject Recognition	—Unverified	0
Linking Entities Across Images and Text	Jul 1, 2015	Entity LinkingImage Retrieval	—Unverified	0
Describing Images using Inferred Visual Dependency Representations	Jul 1, 2015	Object RecognitionText Generation	—Unverified	0
Occlusion Coherence: Detecting and Localizing Occluded Faces	Jun 28, 2015	Face DetectionObject Recognition	CodeCode Available	0
Natural Scene Recognition Based on Superpixels and Deep Boltzmann Machines	Jun 24, 2015	ClusteringHandwritten Digit Recognition	—Unverified	0
A Novel Feature Extraction Method for Scene Recognition Based on Centered Convolutional Restricted Boltzmann Machines	Jun 24, 2015	Object RecognitionScene Recognition	—Unverified	0
A Discriminative Representation of Convolutional Features for Indoor Scene Recognition	Jun 17, 2015	ObjectObject Recognition	—Unverified	0
Multi-path Convolutional Neural Networks for Complex Image Classification	Jun 15, 2015	ClassificationGeneral Classification	CodeCode Available	0

Show:10 25 50

← PrevPage 72 of 82Next →

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