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 3751–3800 of 10420 papers

TitleStatusHype
ExMobileViT: Lightweight Classifier Extension for Mobile Vision Transformer—0
Adversarial Learning of Label Dependency: A Novel Framework for Multi-class Classification—0
Detecting Visually Relevant Sentences for Fine-Grained Classification—0
ExpandNets: Linear Over-parameterization to Train Compact Convolutional Networks—0
BFBox: Searching Face-Appropriate Backbone and Feature Pyramid Network for Face Detector—0
Cluster-Guided Semi-Supervised Domain Adaptation for Imbalanced Medical Image Classification—0
Detecting Spurious Correlations via Robust Visual Concepts in Real and AI-Generated Image Classification—0
clustering an african hairstyle dataset using pca and k-means—0
Be Your Own Best Competitor! Multi-Branched Adversarial Knowledge Transfer—0
Expert-Like Reparameterization of Heterogeneous Pyramid Receptive Fields in Efficient CNNs for Fair Medical Image Classification—0
Experts Don't Cheat: Learning What You Don't Know By Predicting Pairs—0
Explainability-aided Domain Generalization for Image Classification—0
Explainability and Robustness of Deep Visual Classification Models—0
Adversarially Robust Generalization Requires More Data—0
An Analysis of the Expressiveness of Deep Neural Network Architectures Based on Their Lipschitz Constants—0
EXPLAINABLE AI-BASED DYNAMIC FILTER PRUNING OF CONVOLUTIONAL NEURAL NETWORKS—0
Function-Space Regularization for Deep Bayesian Classification—0
Explainable AI (XAI) in Image Segmentation in Medicine, Industry, and Beyond: A Survey—0
Explainable Analysis of Deep Learning Methods for SAR Image Classification—0
Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models—0
Detecting Overfitting via Adversarial Examples—0
An Analysis of Pre-Training on Object Detection—0
Explainable Disease Classification via weakly-supervised segmentation—0
CNN Based Analysis of the Luria’s Alternating Series Test for Parkinson’s Disease Diagnostics—0
Explainable Image Classification with Evidence Counterfactual—0
Explainable Knowledge Distillation for On-device Chest X-Ray Classification—0
Explainable Metric Learning for Deflating Data Bias—0
AdaScale SGD: A Scale-Invariant Algorithm for Distributed Training—0
Explainable unsupervised multi-modal image registration using deep networks—0
Explainers in the Wild: Making Surrogate Explainers Robust to Distortions through Perception—0
Detecting Novelties with Empty Classes—0
Explaining Black-box Model Predictions via Two-level Nested Feature Attributions with Consistency Property—0
A Preliminary Study on Data Augmentation of Deep Learning for Image Classification—0
Explaining Clinical Decision Support Systems in Medical Imaging using Cycle-Consistent Activation Maximization—0
Detecting Localized Adversarial Examples: A Generic Approach using Critical Region Analysis—0
Explaining Convolutional Neural Networks by Tagging Filters—0
Explaining Deep Convolutional Neural Networks for Image Classification by Evolving Local Interpretable Model-agnostic Explanations—0
A Principled Hierarchical Deep Learning Approach to Joint Image Compression and Classification—0
CNNs Avoid Curse of Dimensionality by Learning on Patches—0
Beyond the Visible: Multispectral Vision-Language Learning for Earth Observation—0
AHA! an 'Artificial Hippocampal Algorithm' for Episodic Machine Learning—0
Function-Space Variational Inference for Deep Bayesian Classification—0
CNNs with Multi-Level Attention for Domain Generalization—0
Explaining non-linear Classifier Decisions within Kernel-based Deep Architectures—0
Fusing Deep Convolutional Networks for Large Scale Visual Concept Classification—0
Explaining Representation by Mutual Information—0
Explaining the Black-box Smoothly- A Counterfactual Approach—0
Explaining the Unexplained: Revealing Hidden Correlations for Better Interpretability—0
Fuzzy-aware Loss for Source-free Domain Adaptation in Visual Emotion Recognition—0
Detecting Hypo-plastic Left Heart Syndrome in Fetal Ultrasound via Disease-specific Atlas Maps—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