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 1011–1020 of 2042 papers

Title	Date	Tasks	Status	Hype
Multi-branch and Multi-scale Attention Learning for Fine-Grained Visual Categorization	Mar 20, 2020	Fine-Grained Image ClassificationFine-Grained Image Recognition	CodeCode Available	1
Pose Augmentation: Class-agnostic Object Pose Transformation for Object Recognition	Mar 19, 2020	ObjectObject Recognition	CodeCode Available	1
Ensemble learning in CNN augmented with fully connected subnetworks	Mar 19, 2020	Ensemble LearningImage Classification	CodeCode Available	0
Fabric Surface Characterization: Assessment of Deep Learning-based Texture Representations Using a Challenging Dataset	Mar 16, 2020	Material RecognitionObject Recognition	—Unverified	0
Towards a Framework for Visual Intelligence in Service Robotics: Epistemic Requirements and Gap Analysis	Mar 13, 2020	Object Recognition	—Unverified	0
Equalization Loss for Long-Tailed Object Recognition	Mar 11, 2020	Long-tail LearningObject	CodeCode Available	1
Measurement-driven Analysis of an Edge-Assisted Object Recognition System	Mar 7, 2020	ObjectObject Recognition	—Unverified	0
The iCub multisensor datasets for robot and computer vision applications	Mar 4, 2020	Action RecognitionGeneral Classification	—Unverified	0
Hand-Priming in Object Localization for Assistive Egocentric Vision	Feb 28, 2020	Hand SegmentationMulti-Task Learning	—Unverified	0
Triangle-Net: Towards Robustness in Point Cloud Learning	Feb 27, 2020	3D Classification3D Object Recognition	CodeCode Available	0

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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