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 1626–1650 of 10420 papers

TitleStatusHype
Allowing humans to interactively guide machines where to look does not always improve human-AI team's classification accuracyCode0
On the Convergence of Continual Learning with Adaptive Methods—0
Neural Cellular Automata for Lightweight, Robust and Explainable Classification of White Blood Cell Images—0
PairAug: What Can Augmented Image-Text Pairs Do for Radiology?Code1
GvT: A Graph-based Vision Transformer with Talking-Heads Utilizing Sparsity, Trained from Scratch on Small Datasets—0
Focused Active Learning for Histopathological Image Classification—0
Trustless Audits without Revealing Data or Models—0
Label Propagation for Zero-shot Classification with Vision-Language ModelsCode1
LiDAR-Guided Cross-Attention Fusion for Hyperspectral Band Selection and Image ClassificationCode0
Noisy Label Processing for Classification: A Survey—0
Evaluating Adversarial Robustness: A Comparison Of FGSM, Carlini-Wagner Attacks, And The Role of Distillation as Defense Mechanism—0
Dendrites endow artificial neural networks with accurate, robust and parameter-efficient learning—0
Meta Invariance Defense Towards Generalizable Robustness to Unknown Adversarial Attacks—0
FACTUAL: A Novel Framework for Contrastive Learning Based Robust SAR Image Classification—0
A Methodology to Study the Impact of Spiking Neural Network Parameters considering Event-Based Automotive Data—0
Sparse Concept Bottleneck Models: Gumbel Tricks in Contrastive LearningCode1
A Novel Approach to Breast Cancer Histopathological Image Classification Using Cross-Colour Space Feature Fusion and Quantum-Classical Stack Ensemble Method—0
Guarantees of confidentiality via Hammersley-Chapman-Robbins boundsCode0
Non-negative Subspace Feature Representation for Few-shot Learning in Medical Imaging—0
DeiT-LT Distillation Strikes Back for Vision Transformer Training on Long-Tailed DatasetsCode1
Visual Concept Connectome (VCC): Open World Concept Discovery and their Interlayer Connections in Deep Models—0
Smooth Deep SaliencyCode0
Beyond Image Super-Resolution for Image Recognition with Task-Driven Perceptual LossCode2
A Universal Knowledge Embedded Contrastive Learning Framework for Hyperspectral Image ClassificationCode0
A noisy elephant in the room: Is your out-of-distribution detector robust to label noise?Code0
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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