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 1676–1700 of 2042 papers

Title	Date	Tasks	Status	Hype
Pairwise Decomposition of Image Sequences for Active Multi-View Recognition	May 26, 2016	Object Recognition	—Unverified	0
Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning	May 25, 2016	Object RecognitionVideo Prediction	CodeCode Available	1
FPNN: Field Probing Neural Networks for 3D Data	May 20, 2016	3D geometry3D Object Recognition	CodeCode Available	0
Hierarchical Piecewise-Constant Super-regions	May 19, 2016	DenoisingForm	—Unverified	0
Dual Local-Global Contextual Pathways for Recognition in Aerial Imagery	May 18, 2016	Object RecognitionRoad Segmentation	—Unverified	0
Incremental Robot Learning of New Objects with Fixed Update Time	May 17, 2016	Active LearningGeneral Classification	CodeCode Available	0
Going Deeper into Action Recognition: A Survey	May 16, 2016	Action AnalysisAction Recognition	—Unverified	0
An Empirical Study and Analysis of Generalized Zero-Shot Learning for Object Recognition in the Wild	May 13, 2016	Few-Shot LearningGeneralized Zero-Shot Learning	CodeCode Available	0
A New Manifold Distance Measure for Visual Object Categorization	May 12, 2016	ClusteringObject	—Unverified	0
ASP Vision: Optically Computing the First Layer of Convolutional Neural Networks using Angle Sensitive Pixels	May 11, 2016	Face IdentificationObject Recognition	—Unverified	0
Measurement Bounds for Sparse Signal Reconstruction with Multiple Side Information	May 10, 2016	compressed sensingObject Recognition	—Unverified	0
A Theoretical Analysis of Deep Neural Networks for Texture Classification	May 9, 2016	ClassificationGeneral Classification	—Unverified	0
Learning Attributes Equals Multi-Source Domain Generalization	May 3, 2016	AttributeDomain Generalization	—Unverified	0
1 Million Captioned Dutch Newspaper Images	May 1, 2016	ArticlesData-to-Text Generation	—Unverified	0
Zero-shot object prediction using semantic scene knowledge	Apr 27, 2016	ObjectObject Recognition	—Unverified	0
Are Face and Object Recognition Independent? A Neurocomputational Modeling Exploration	Apr 26, 2016	Object Recognition	—Unverified	0
Modeling the Contribution of Central Versus Peripheral Vision in Scene, Object, and Face Recognition	Apr 25, 2016	Face RecognitionObject Recognition	—Unverified	0
Humans and deep networks largely agree on which kinds of variation make object recognition harder	Apr 21, 2016	ObjectObject Recognition	—Unverified	0
Automatic Graphic Logo Detection via Fast Region-based Convolutional Networks	Apr 20, 2016	Data AugmentationLogo Recognition	—Unverified	0
Can Boosting with SVM as Week Learners Help?	Apr 18, 2016	ObjectObject Categorization	—Unverified	0
Invariant feature extraction from event based stimuli	Apr 15, 2016	Object Recognition	—Unverified	0
DTM: Deformable Template Matching	Apr 12, 2016	Object RecognitionTemplate Matching	—Unverified	0
Orientation-boosted Voxel Nets for 3D Object Recognition	Apr 12, 2016	3D Object RecognitionClassification	—Unverified	0
T-CNN: Tubelets with Convolutional Neural Networks for Object Detection from Videos	Apr 9, 2016	Novel Object DetectionObject	CodeCode Available	0
Edge Detection Based Shape Identification	Apr 7, 2016	Edge DetectionObject	—Unverified	0

Show:10 25 50

← PrevPage 68 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