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 1801–1810 of 2042 papers

Title	Date	Tasks	Status
SegICP: Integrated Deep Semantic Segmentation and Pose Estimation	Mar 5, 2017	Object RecognitionPoint Cloud Registration	CodeCode Available
Multiple Object Recognition with Visual Attention	Dec 24, 2014	ObjectObject Recognition	CodeCode Available
SharpNet: Fast and Accurate Recovery of Occluding Contours in Monocular Depth Estimation	May 21, 2019	Depth EstimationDepth Prediction	CodeCode Available
Multi-level 3D CNN for Learning Multi-scale Spatial Features	May 30, 2018	3D Object RecognitionObject	CodeCode Available
Image Captioning using Deep Neural Architectures	Jan 17, 2018	Image CaptioningMachine Translation	CodeCode Available
Improved object recognition using neural networks trained to mimic the brain's statistical properties	May 25, 2019	ObjectObject Categorization	CodeCode Available
Multiscale Dubuc: A New Similarity Measure for Time Series	Nov 15, 2024	Dynamic Time WarpingObject Recognition	CodeCode Available
Unsupervised Domain Adaptation through Inter-modal Rotation for RGB-D Object Recognition	Apr 21, 2020	Domain AdaptationObject Categorization	CodeCode Available
A Dataset for Crucial Object Recognition in Blind and Low-Vision Individuals' Navigation	Jul 23, 2024	Object Recognition	CodeCode Available
ImageNet Classification with Deep Convolutional Neural Networks	Dec 1, 2012	General ClassificationGPU	CodeCode Available

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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