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 8251–8275 of 10420 papers

TitleStatusHype
A Semantics-Guided Class Imbalance Learning Model for Zero-Shot Classification—0
Multi-Path Learnable Wavelet Neural Network for Image Classification—0
Confidence Regularized Self-TrainingCode1
Calibration of Deep Probabilistic Models with Decoupled Bayesian Neural NetworksCode0
Feature Learning to Automatically Assess Radiographic Knee Osteoarthritis Severity—0
Mish: A Self Regularized Non-Monotonic Activation FunctionCode0
Learning Filter Basis for Convolutional Neural Network CompressionCode1
Image Colorization By Capsule Networks—0
ColorNet -- Estimating Colorfulness in Natural ImagesCode0
Evaluating Defensive Distillation For Defending Text Processing Neural Networks Against Adversarial ExamplesCode0
DomainSiam: Domain-Aware Siamese Network for Visual Object Tracking—0
Density estimation in representation space to predict model uncertainty—0
Saccader: Improving Accuracy of Hard Attention Models for VisionCode0
Dynamic Graph Message Passing NetworksCode1
Representing text as abstract images enables image classifiers to also simultaneously classify text—0
Adversarial Defense by Suppressing High-frequency ComponentsCode0
Adaptative Inference Cost With Convolutional Neural Mixture Models—0
NLNL: Negative Learning for Noisy LabelsCode0
Demystifying Learning Rate Policies for High Accuracy Training of Deep Neural NetworksCode1
Verification of Neural Network Control Policy Under Persistent Adversarial Perturbation—0
Gradient Weighted Superpixels for Interpretability in CNNs—0
Symmetric Cross Entropy for Robust Learning with Noisy LabelsCode0
SCARLET-NAS: Bridging the Gap between Stability and Scalability in Weight-sharing Neural Architecture SearchCode0
Needles in Haystacks: On Classifying Tiny Objects in Large ImagesCode0
Sparse Bayesian approach for metric learning in latent spaceCode0
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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
5DaViT-HTop 1 Accuracy90.2—Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 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
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified