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 3501–3550 of 10419 papers

TitleStatusHype
Shape-Aware Fine-Grained Classification of Erythroid CellsCode1
Sparse Mixture Once-for-all Adversarial Training for Efficient In-Situ Trade-Off Between Accuracy and Robustness of DNNs—0
Attribute-Guided Multi-Level Attention Network for Fine-Grained Fashion RetrievalCode0
Langevin algorithms for very deep Neural Networks with application to image classificationCode0
Saliency-Augmented Memory Completion for Continual LearningCode0
LMFLOSS: A Hybrid Loss For Imbalanced Medical Image ClassificationCode0
Hyperspherical Loss-Aware Ternary Quantization—0
Image Classification with Small Datasets: Overview and BenchmarkCode1
When are Lemons Purple? The Concept Association Bias of Vision-Language Models—0
Understanding and Improving the Role of Projection Head in Self-Supervised Learning—0
On Calibrating Semantic Segmentation Models: Analyses and An AlgorithmCode1
Reversible Column NetworksCode2
Class Prototype-based Cleaner for Label Noise LearningCode0
Decision-making and control with diffractive optical networksCode0
MaskingDepth: Masked Consistency Regularization for Semi-supervised Monocular Depth EstimationCode1
Temporal Output Discrepancy for Loss Estimation-based Active Learning—0
Calibrating Deep Neural Networks using Explicit Regularisation and Dynamic Data Pruning—0
Galaxy Image Classification using Hierarchical Data Learning with Weighted Sampling and Label SmoothingCode0
DDIPNet and DDIPNet+: Discriminant Deep Image Prior Networks for Remote Sensing Image Classification—0
Unified Framework for Histopathology Image Augmentation and Classification via Generative Models—0
Rethinking Label Smoothing on Multi-hop Question AnsweringCode0
Improving Pre-Trained Weights Through Meta-Heuristics Fine-TuningCode0
Style-Hallucinated Dual Consistency Learning: A Unified Framework for Visual Domain GeneralizationCode1
A Framework for Generalizing Critical Heat Flux Detection Models Using Unsupervised Image-to-Image Translation—0
Scattering-induced entropy boost for highly-compressed optical sensing and encryption—0
Test-time Adaptation in the Dynamic World with Compound Domain Knowledge Management—0
From Xception to NEXcepTion: New Design Decisions and Neural Architecture SearchCode0
Instance-dependent Label Distribution Estimation for Learning with Label NoiseCode0
Better May Not Be Fairer: A Study on Subgroup Discrepancy in Image ClassificationCode0
Convolution-enhanced Evolving Attention NetworksCode1
Bayesian posterior approximation with stochastic ensemblesCode0
Backdoor Attack Detection in Computer Vision by Applying Matrix Factorization on the Weights of Deep Networks—0
CLIPPO: Image-and-Language Understanding from Pixels Only—0
Learning to Detect Semantic Boundaries with Image-level Class Labels—0
Efficient Self-supervised Learning with Contextualized Target Representations for Vision, Speech and LanguageCode1
SAIF: Sparse Adversarial and Imperceptible Attack Framework—0
Domain Generalization by Learning and Removing Domain-specific FeaturesCode1
Design-time Fashion Popularity Forecasting in VR Environments—0
Reproducible scaling laws for contrastive language-image learningCode1
Post-hoc Uncertainty Learning using a Dirichlet Meta-ModelCode1
GPViT: A High Resolution Non-Hierarchical Vision Transformer with Group PropagationCode1
Adversarial Attacks and Defences for Skin Cancer Classification—0
CAT: Learning to Collaborate Channel and Spatial Attention from Multi-Information Fusion—0
Can a face tell us anything about an NBA prospect? -- A Deep Learning approach—0
Losses over Labels: Weakly Supervised Learning via Direct Loss ConstructionCode0
Regularized Optimal Transport Layers for Generalized Global Pooling OperationsCode1
Synthetic Image Data for Deep Learning—0
Quantum Phase Recognition using Quantum Tensor Networks—0
A Neural ODE Interpretation of Transformer Layers—0
General Adversarial Defense Against Black-box Attacks via Pixel Level and Feature Level Distribution Alignments—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