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 5976–6000 of 10420 papers

TitleStatusHype
Visual Representation Learning with Self-Supervised Attention for Low-Label High-data RegimeCode0
Parallel Rectangle Flip Attack: A Query-based Black-box Attack against Object Detection—0
Enabling Deep Learning on Edge Devices through Filter Pruning and Knowledge Transfer—0
Investigating the Potential of Auxiliary-Classifier GANs for Image Classification in Low Data Regimes—0
Dangerous Cloaking: Natural Trigger based Backdoor Attacks on Object Detectors in the Physical World—0
Signal Strength and Noise Drive Feature Preference in CNN Image ClassifiersCode0
Deep Cervix Model Development from Heterogeneous and Partially Labeled Image Datasets—0
Explainable Ensemble Machine Learning for Breast Cancer Diagnosis based on Ultrasound Image Texture FeaturesCode0
Distillation from heterogeneous unlabeled collections—0
Behavior of Mini-Batch Optimization for Training Deep Neural Networks on Large Datasets—0
Landscape of Neural Architecture Search across sensors: how much do they differ ?—0
YOLO -- You only look 10647 times—0
Discrete Simulation Optimization for Tuning Machine Learning Method Hyperparameters—0
Neighborhood Region Smoothing Regularization for Finding Flat Minima In Deep Neural Networks—0
ALA: Naturalness-aware Adversarial Lightness Attack—0
A Text-Image Pair Is not Enough: Language-Vision Relation Inference with Auxiliary Modality Translation—0
Multi-level Second-order Few-shot LearningCode0
Taylor-Lagrange Neural Ordinary Differential Equations: Toward Fast Training and Evaluation of Neural ODEsCode0
Pushing the limits of self-supervised ResNets: Can we outperform supervised learning without labels on ImageNet?Code0
Conditional Variational Autoencoder with Balanced Pre-training for Generative Adversarial Networks—0
Preventing Manifold Intrusion with Locality: Local MixupCode0
Competing Mutual Information Constraints with Stochastic Competition-based Activations for Learning Diversified Representations—0
Avoiding Overfitting: A Survey on Regularization Methods for Convolutional Neural Networks—0
ThreshNet: An Efficient DenseNet Using Threshold Mechanism to Reduce ConnectionsCode0
Invariance encoding in sliced-Wasserstein space for image classification with limited training dataCode0
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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