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 1161–1170 of 2042 papers

Title	Date	Tasks	Status
What is the Best Feature Learning Procedure in Hierarchical Recognition Architectures?	Jun 5, 2016	Object RecognitionUnsupervised Pre-training	—Unverified
What's in a Name? Beyond Class Indices for Image Recognition	Apr 5, 2023	ClusteringLanguage Modelling	—Unverified
What's in my Room? Object Recognition on Indoor Panoramic Images	Oct 14, 2019	Instance SegmentationObject	—Unverified
What takes the brain so long: Object recognition at the level of minimal images develops for up to seconds of presentation time	Jun 9, 2020	Decision MakingObject Recognition	—Unverified
What you need to know about the state-of-the-art computational models of object-vision: A tour through the models	Jul 10, 2014	Object Recognition	—Unverified
When Regression Meets Manifold Learning for Object Recognition and Pose Estimation	May 16, 2018	Multi-Task LearningObject Recognition	—Unverified
Why my photos look sideways or upside down? Detecting Canonical Orientation of Images using Convolutional Neural Networks	Dec 4, 2017	Object RecognitionScene Understanding	—Unverified
Why The Brain Separates Face Recognition From Object Recognition	Dec 1, 2011	Face IdentificationFace Recognition	—Unverified
Winograd Convolution for Deep Neural Networks: Efficient Point Selection	Jan 25, 2022	Image SegmentationObject Recognition	—Unverified
X-model: Improving Data Efficiency in Deep Learning with A Minimax Model	Oct 9, 2021	Age Estimationmodel	—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