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 331–340 of 2042 papers

Title	Date	Tasks	Status
A Generic Regression Framework for Pose Recognition on Color and Depth Images	Sep 23, 2017	General ClassificationObject Recognition	—Unverified
Active Gaze Behavior Boosts Self-Supervised Object Learning	Nov 4, 2024	ObjectObject Recognition	—Unverified
Compressing Deep Convolutional Networks using Vector Quantization	Dec 18, 2014	ClassificationClustering	—Unverified
Consistency of Silhouettes and Their Duals	Jun 1, 2016	Camera CalibrationObject	—Unverified
Context-LGM: Leveraging Object-Context Relation for Context-Aware Object Recognition	Oct 8, 2021	Emotion RecognitionObject	—Unverified
Are Face and Object Recognition Independent? A Neurocomputational Modeling Exploration	Apr 26, 2016	Object Recognition	—Unverified
Are Deep Neural Networks Adequate Behavioural Models of Human Visual Perception?	May 26, 2023	ObjectObject Recognition	—Unverified
Complete End-To-End Low Cost Solution To a 3D Scanning System with Integrated Turntable	Sep 3, 2017	3D ReconstructionObject Recognition	—Unverified
A recurrent multi-scale approach to RBG-D Object Recognition	Jul 31, 2018	ObjectObject Recognition	—Unverified
A Convolutional Neural Network based Live Object Recognition System as Blind Aid	Nov 26, 2018	Objectobject-detection	—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