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 10351–10375 of 10420 papers

TitleStatusHype
Striving for Simplicity: The All Convolutional NetCode0
STREAMLINE: Streaming Active Learning for Realistic Multi-Distributional SettingsCode0
Understanding and Improving Group NormalizationCode0
Self-Supervised Feature Learning of 1D Convolutional Neural Networks with Contrastive Loss for Eating Detection Using an In-Ear MicrophoneCode0
StrassenNets: Deep Learning with a Multiplication BudgetCode0
Understanding Architectures Learnt by Cell-based Neural Architecture SearchCode0
Signatures of Bayesian inference emerge from energy efficient synapsesCode0
Stochastic Pooling for Regularization of Deep Convolutional Neural NetworksCode0
Understanding Deep Architectures by Visual SummariesCode0
Understanding deep learning requires rethinking generalizationCode0
Understanding Gaussian Attention Bias of Vision Transformers Using Effective Receptive FieldsCode0
Micro-Batch Training with Batch-Channel Normalization and Weight StandardizationCode0
Stochastic Optimization of Plain Convolutional Neural Networks with Simple methodsCode0
Understanding How Image Quality Affects Deep Neural NetworksCode0
Stochastic Kernel Regularisation Improves Generalisation in Deep Kernel MachinesCode0
Signal Strength and Noise Drive Feature Preference in CNN Image ClassifiersCode0
SCARLET-NAS: Bridging the Gap between Stability and Scalability in Weight-sharing Neural Architecture SearchCode0
Understanding Robustness of Parameter-Efficient Tuning for Image ClassificationCode0
Scalable Marginal Likelihood Estimation for Model Selection in Deep LearningCode0
Understanding Robustness of Visual State Space Models for Image ClassificationCode0
Stochastic Gradient Push for Distributed Deep LearningCode0
Understanding Local Robustness of Deep Neural Networks under Natural VariationsCode0
SIFT-DBT: Self-supervised Initialization and Fine-Tuning for Imbalanced Digital Breast Tomosynthesis Image ClassificationCode0
Self-Paced Learning with Adaptive Deep Visual EmbeddingsCode0
Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional NetworksCode0
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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