SOTAVerified

Image Classification

Image Classification is a fundamental task in vision recognition that aims to understand and categorize an image as a whole under a specific label. Unlike object detection, which involves classification and location of multiple objects within an image, image classification typically pertains to single-object images. When the classification becomes highly detailed or reaches instance-level, it is often referred to as image retrieval, which also involves finding similar images in a large database.

Source: Metamorphic Testing for Object Detection Systems

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 7626–7650 of 10420 papers

TitleStatusHype
A deep primal-dual proximal network for image restoration—0
Learning ordered pooling weights in image classificationCode0
Image Analysis Based on Nonnegative/Binary Matrix Factorization—0
Estimation with Uncertainty via Conditional Generative Adversarial Networks—0
Robust and Accurate Authorship Attribution via Program Normalization—0
Language to Network: Conditional Parameter Adaptation with Natural Language Descriptions—0
Robustifying the Deployment of tinyML Models for Autonomous mini-vehicles—0
SeqVAT: Virtual Adversarial Training for Semi-Supervised Sequence Labeling—0
HACT-Net: A Hierarchical Cell-to-Tissue Graph Neural Network for Histopathological Image Classification—0
Extracurricular Learning: Knowledge Transfer Beyond Empirical Distribution—0
Training highly effective connectivities within neural networks with randomly initialized, fixed weightsCode0
Explainable 3D Convolutional Neural Networks by Learning Temporal Transformations—0
Conditional Classification: A Solution for Computational Energy Reduction—0
Matrix Shuffle-Exchange Networks for Hard 2D TasksCode0
Harnessing Adversarial Distances to Discover High-Confidence ErrorsCode0
Active Ensemble Deep Learning for Polarimetric Synthetic Aperture Radar Image Classification—0
Compositional Convolutional Neural Networks: A Robust and Interpretable Model for Object Recognition under Occlusion—0
Performing Image Classification for 10 Different Monkey Species using CNN—0
Frequency learning for image classification—0
Unsupervised Deep Representation Learning and Few-Shot Classification of PolSAR Images—0
An Evoked Potential-Guided Deep Learning Brain Representation For Visual Classification—0
ReMarNet: Conjoint Relation and Margin Learning for Small-Sample Image ClassificationCode0
End-to-end training of deep kernel map networks for image classification—0
Not all Failure Modes are Created Equal: Training Deep Neural Networks for Explicable (Mis)Classification—0
​4S-DT: Self Supervised Super Sample Decomposition for Transfer learning with application to COVID-19 detection—0
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All datasetsImageNetCIFAR-10CIFAR-100STL-10ObjectNetMNISTSVHNiNaturalist 2018ImageNet ReaLFlowers-102Clothing1Mmini WebVision 1.0

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91—Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98—Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94—Unverified
4DaViT-GTop 1 Accuracy90.4—Unverified
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2—Unverified
6DaViT-HTop 1 Accuracy90.2—Unverified
7SwinV2-GTop 1 Accuracy90.17—Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1—Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05—Unverified
10RevCol-HTop 1 Accuracy90—Unverified