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 1741–1750 of 2042 papers

Title	Date	Tasks	Status
ChoiceNet: CNN learning through choice of multiple feature map representations	Apr 20, 2019	Object RecognitionSemantic Segmentation	—Unverified
Chosen methods of improving small object recognition with weak recognizable features	Aug 29, 2022	DiversityObject	—Unverified
CIFAR10 to Compare Visual Recognition Performance between Deep Neural Networks and Humans	Nov 18, 2018	General ClassificationObject	—Unverified
Classification and Geometry of General Perceptual Manifolds	Oct 17, 2017	ClassificationGeneral Classification	—Unverified
Classifier-to-Generator Attack: Estimation of Training Data Distribution from Classifier	Jan 1, 2018	ClassificationFace Recognition	—Unverified
Classifying Malware Images with Convolutional Neural Network Models	Oct 30, 2020	ClassificationGeneral Classification	—Unverified
Class incremental learning for video action classification	Sep 19, 2021	Action ClassificationAction Recognition In Videos	—Unverified
Class-specific Anchoring Proposal for 3D Object Recognition in LIDAR and RGB Images	Jul 22, 2019	3D Object RecognitionAutonomous Driving	—Unverified
CLIP-Nav: Using CLIP for Zero-Shot Vision-and-Language Navigation	Nov 30, 2022	DiversityInstruction Following	—Unverified
Cloud based Scalable Object Recognition from Video Streams using Orientation Fusion and Convolutional Neural Networks	Jun 19, 2021	ObjectObject Recognition	—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