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 871–880 of 2042 papers

Title	Date	Tasks	Status
Co-training Transformer with Videos and Images Improves Action Recognition	Dec 14, 2021	Action ClassificationAction Recognition	—Unverified
A large comparison of feature-based approaches for buried target classification in forward-looking ground-penetrating radar	Feb 9, 2017	General ClassificationObject Recognition	—Unverified
Discriminate-and-Rectify Encoders: Learning from Image Transformation Sets	Mar 14, 2017	Face VerificationObject Recognition	—Unverified
Guided SAM: Label-Efficient Part Segmentation	Jan 13, 2025	ObjectObject Recognition	—Unverified
GuideMe: A Mobile Application based on Global Positioning System and Object Recognition Towards a Smart Tourist Guide	May 27, 2021	Object Recognition	—Unverified
Guiding Visual Attention in Deep Convolutional Neural Networks Based on Human Eye Movements	Jun 21, 2022	Face DetectionObject Recognition	—Unverified
Discrete Potts Model for Generating Superpixels on Noisy Images	Mar 20, 2018	DenoisingObject Recognition	—Unverified
Hallucinating Saliency Maps for Fine-Grained Image Classification for Limited Data Domains	Jul 24, 2020	ClassificationFine-Grained Image Classification	—Unverified
Brain Cancer Segmentation Using YOLOv5 Deep Neural Network	Dec 27, 2022	GPUInstance Segmentation	—Unverified
An Efficient Semi-Automated Scheme for Infrastructure LiDAR Annotation	Jan 25, 2023	Autonomous DrivingMulti-Object Tracking	—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