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 1081–1090 of 2042 papers

Title	Date	Tasks	Status
Understanding Adversarial Examples Through Deep Neural Network's Response Surface and Uncertainty Regions	Jun 30, 2021	Classificationimage-classification	—Unverified
Understanding Bayesian Rooms Using Composite 3D Object Models	Jun 1, 2013	ObjectObject Recognition	—Unverified
Understanding How Blind Users Handle Object Recognition Errors: Strategies and Challenges	Aug 6, 2024	ObjectObject Recognition	—Unverified
Understanding Low- and High-Level Contributions to Fixation Prediction	Oct 1, 2017	Object RecognitionPrediction	—Unverified
Understanding Tools: Task-Oriented Object Modeling, Learning and Recognition	Jun 1, 2015	ObjectObject Recognition	—Unverified
Unity of Opposites: SelfNorm and CrossNorm for Model Robustness	Jan 1, 2021	Object RecognitionUnity	—Unverified
Universal adversarial perturbation for remote sensing images	Feb 22, 2022	ClassificationDecoder	—Unverified
Unpaired Image Captioning by Image-level Weakly-Supervised Visual Concept Recognition	Mar 7, 2022	Graph Neural NetworkImage Captioning	—Unverified
Unsupervised AER Object Recognition Based on Multiscale Spatio-Temporal Features and Spiking Neurons	Nov 19, 2019	Object Recognition	—Unverified
Unsupervised Cross-Domain Recognition by Identifying Compact Joint Subspaces	Sep 5, 2015	Domain AdaptationObject Recognition	—Unverified

Show:10 25 50

← PrevPage 109 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