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 1326–1350 of 2042 papers

Title	Date	Tasks	Status
Seeing Beyond Appearance - Mapping Real Images into Geometrical Domains for Unsupervised CAD-based Recognition	Oct 9, 2018	DenoisingDomain Adaptation	—Unverified
Weighted Sigmoid Gate Unit for an Activation Function of Deep Neural Network	Oct 3, 2018	Image RestorationObject	—Unverified
Knowledge-guided Semantic Computing Network	Sep 29, 2018	Adversarial RobustnessObject Recognition	—Unverified
Deep learning systems as complex networks	Sep 28, 2018	Deep LearningNatural Language Understanding	—Unverified
DEEP HIERARCHICAL MODEL FOR HIERARCHICAL SELECTIVE CLASSIFICATION AND ZERO SHOT LEARNING	Sep 27, 2018	ClassificationObject Recognition	—Unverified
Semantic Topic Analysis of Traffic Camera Images	Sep 27, 2018	Data CompressionObject Recognition	—Unverified
Semantic and structural image segmentation for prosthetic vision	Sep 25, 2018	Image SegmentationObject	—Unverified
Learning to Localize and Align Fine-Grained Actions to Sparse Instructions	Sep 22, 2018	ObjectObject Recognition	—Unverified
Transparency and Explanation in Deep Reinforcement Learning Neural Networks	Sep 17, 2018	Atari GamesDeep Reinforcement Learning	—Unverified
Periocular Recognition Using CNN Features Off-the-Shelf	Sep 17, 2018	Object Recognition	—Unverified
Object-sensitive Deep Reinforcement Learning	Sep 17, 2018	Atari GamesDeep Reinforcement Learning	—Unverified
A Fog Robotic System for Dynamic Visual Servoing	Sep 16, 2018	Object Recognition	—Unverified
Non-iterative recomputation of dense layers for performance improvement of DCNN	Sep 14, 2018	Object Recognition	—Unverified
Context-Dependent Diffusion Network for Visual Relationship Detection	Sep 11, 2018	DiversityObject	—Unverified
A Variational Feature Encoding Method of 3D Object for Probabilistic Semantic SLAM	Aug 30, 2018	Bayesian InferenceObject	—Unverified
AAD: Adaptive Anomaly Detection through traffic surveillance videos	Aug 29, 2018	Action DetectionActivity Detection	—Unverified
Generalisation in humans and deep neural networks	Aug 27, 2018	Object Recognition	CodeCode Available
PVNet: A Joint Convolutional Network of Point Cloud and Multi-View for 3D Shape Recognition	Aug 23, 2018	3D Object Recognition3D Shape Classification	CodeCode Available
VERAM: View-Enhanced Recurrent Attention Model for 3D Shape Classification	Aug 20, 2018	3D Shape ClassificationClassification	—Unverified
A Domain Guided CNN Architecture for Predicting Age from Structural Brain Images	Aug 11, 2018	Object Recognition	CodeCode Available
Parsing Geometry Using Structure-Aware Shape Templates	Aug 3, 2018	ObjectObject Recognition	CodeCode Available
Saliency for Fine-grained Object Recognition in Domains with Scarce Training Data	Aug 1, 2018	Object Recognition	—Unverified
Energy-based Tuning of Convolutional Neural Networks on Multi-GPUs	Aug 1, 2018	GPUObject Recognition	—Unverified
A recurrent multi-scale approach to RBG-D Object Recognition	Jul 31, 2018	ObjectObject Recognition	—Unverified
Dynamic reshaping of functional brain networks during visual object recognition	Jul 31, 2018	EEGElectroencephalogram (EEG)	—Unverified

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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