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 1076–1100 of 2042 papers

Title	Date	Tasks	Status
Fractional order graph neural network	Jan 5, 2020	global-optimizationGraph Neural Network	—Unverified
UW-NET: AN INCEPTION-ATTENTION NETWORK FOR UNDERWATER IMAGE CLASSIFICATION	Jan 1, 2020	ClassificationGeneral Classification	—Unverified
KNN-Based Automatic Cropping for Improved Threat Object Recognition in X-Ray Security Images	Dec 31, 2019	Anomaly DetectionObject Recognition	—Unverified
Experiments with mmWave Automotive Radar Test-bed	Dec 29, 2019	Object Recognition	CodeCode Available
Application of Deep Learning in Generating Desired Design Options: Experiments Using Synthetic Training Dataset	Dec 28, 2019	Object Recognition	—Unverified
Importance Filtered Cross-Domain Adaptation	Dec 24, 2019	Domain AdaptationObject Recognition	—Unverified
Interactive Open-Ended Learning for 3D Object Recognition	Dec 19, 2019	3D Object RecognitionObject	—Unverified
Towards Contextual Learning in Few-shot Object Classification	Dec 13, 2019	ClassificationFew-Shot Learning	—Unverified
Deep-learning-based classification and retrieval of components of a process plant from segmented point clouds	Dec 13, 2019	General ClassificationObject Recognition	—Unverified
L3DOC: Lifelong 3D Object Classification	Dec 12, 2019	3D geometry3D Object Classification	—Unverified
Toward Better Understanding of Saliency Prediction in Augmented 360 Degree Videos	Dec 12, 2019	Object RecognitionOptical Flow Estimation	—Unverified
Associative Alignment for Few-shot Image Classification	Dec 11, 2019	ClassificationDomain Adaptation	CodeCode Available
Detecting and Correcting Adversarial Images Using Image Processing Operations	Dec 11, 2019	BIG-bench Machine LearningObject Recognition	—Unverified
Object Recognition with Human in the Loop Intelligent Frameworks	Dec 11, 2019	ObjectObject Recognition	—Unverified
Improved Few-Shot Visual Classification	Dec 7, 2019	ClassificationFew-Shot Image Classification	—Unverified
300 GHz Radar Object Recognition based on Deep Neural Networks and Transfer Learning	Dec 6, 2019	ObjectObject Recognition	—Unverified
Video to Events: Recycling Video Datasets for Event Cameras	Dec 6, 2019	Object RecognitionSemantic Segmentation	CodeCode Available
Continual egocentric object recognition	Dec 6, 2019	Active LearningNovelty Detection	CodeCode Available
A Neural Spiking Approach Compared to Deep Feedforward Networks on Stepwise Pixel Erasement	Dec 6, 2019	ClassificationGeneral Classification	—Unverified
ObjectNet: A large-scale bias-controlled dataset for pushing the limits of object recognition models	Dec 1, 2019	BIG-bench Machine LearningImage Classification	—Unverified
Deliberative Explanations: visualizing network insecurities	Dec 1, 2019	AttributeObject Recognition	CodeCode Available
Representation Learning on Unit Ball with 3D Roto-Translational Equivariance	Nov 30, 2019	3D Object RecognitionObject Recognition	—Unverified
Motion Equivariance OF Event-based Camera Data with the Temporal Normalization Transform	Nov 28, 2019	Object Recognition	—Unverified
GBCNs: Genetic Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs	Nov 25, 2019	Face RecognitionObject Recognition	—Unverified
Fine-grained Attention and Feature-sharing Generative Adversarial Networks for Single Image Super-Resolution	Nov 25, 2019	Generative Adversarial NetworkImage Super-Resolution	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