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 321–330 of 2042 papers

Title	Date	Tasks	Status
A hierarchical framework for object recognition	Oct 28, 2014	ObjectObject Recognition	—Unverified
A Review on Near Duplicate Detection of Images using Computer Vision Techniques	Sep 7, 2020	object-detectionObject Detection	—Unverified
Active Object Perceiver: Recognition-guided Policy Learning for Object Searching on Mobile Robots	Jul 30, 2018	Deep Reinforcement LearningObject	—Unverified
Y-GAN: A Generative Adversarial Network for Depthmap Estimation from Multi-camera Stereo Images	Jun 3, 2019	3D Object RecognitionGenerative Adversarial Network	—Unverified
A Review of Pulse-Coupled Neural Network Applications in Computer Vision and Image Processing	Jun 1, 2024	Edge DetectionImage Compression	—Unverified
A Review of methods for Textureless Object Recognition	Oct 31, 2019	Edge DetectionObject	—Unverified
Agricultural Object Detection with You Look Only Once (YOLO) Algorithm: A Bibliometric and Systematic Literature Review	Jan 18, 2024	ArticlesObject	—Unverified
A Resilient Image Matching Method with an Affine Invariant Feature Detector and Descriptor	Dec 29, 2017	3D Object ReconstructionObject Recognition	—Unverified
Are Labels Always Necessary for Classifier Accuracy Evaluation?	Jul 6, 2020	Object Recognitionregression	—Unverified
A Generic Regression Framework for Pose Recognition on Color and Depth Images	Sep 23, 2017	General ClassificationObject Recognition	—Unverified

Show:10 25 50

← PrevPage 33 of 205Next →

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