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 1611–1620 of 2042 papers

Title	Date	Tasks	Status
A Novel mapping for visual to auditory sensory substitution	Jun 14, 2021	Object Recognition	—Unverified
An Overview Of 3D Object Detection	Oct 29, 2020	3D Object DetectionObject	—Unverified
Answer-Type Prediction for Visual Question Answering	Jun 1, 2016	Object RecognitionPrediction	—Unverified
Anytime Recognition of Objects and Scenes	Jun 1, 2014	General ClassificationObject Recognition	—Unverified
A Performance Evaluation of Correspondence Grouping Methods for 3D Rigid Data Matching	Jul 5, 2019	3D Object RecognitionObject Recognition	—Unverified
A Poodle or a Dog? Evaluating Automatic Image Annotation Using Human Descriptions at Different Levels of Granularity	Aug 1, 2014	Object Recognition	—Unverified
Application of 2D Homography for High Resolution Traffic Data Collection using CCTV Cameras	Jan 14, 2024	Camera CalibrationObject Recognition	—Unverified
Application of Deep Learning in Generating Desired Design Options: Experiments Using Synthetic Training Dataset	Dec 28, 2019	Object Recognition	—Unverified
Application of Faster R-CNN model on Human Running Pattern Recognition	Nov 13, 2018	Object Recognition	—Unverified
Applications of Probabilistic Programming (Master's thesis, 2015)	May 31, 2016	Object RecognitionProbabilistic Programming	—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