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

Showing 1000110025 of 10420 papers

TitleStatusHype
ShapeShifter: Robust Physical Adversarial Attack on Faster R-CNN Object DetectorCode0
Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial NetworksCode0
Will Large-scale Generative Models Corrupt Future Datasets?Code0
Towards Better Multi-head Attention via Channel-wise Sample PermutationCode0
The Weighting Game: Evaluating Quality of Explainability MethodsCode0
Towards Bridging the Performance Gaps of Joint Energy-based ModelsCode0
ComFe: Interpretable Image Classifiers With Foundation Models, Transformers and Component FeaturesCode0
Towards Calibrated Hyper-Sphere Representation via Distribution Overlap Coefficient for Long-tailed LearningCode0
Neural Parameter Allocation SearchCode0
ViC-MAE: Self-Supervised Representation Learning from Images and Video with Contrastive Masked AutoencodersCode0
The Weighted Tsetlin Machine: Compressed Representations with Weighted ClausesCode0
Towards Debugging Deep Neural Networks by Generating Speech UtterancesCode0
Unsupervised Contrastive Analysis for Salient Pattern Detection using Conditional Diffusion ModelsCode0
Unsupervised Cross-Domain Feature Extraction for Single Blood Cell Image ClassificationCode0
A Large-scale Study of Representation Learning with the Visual Task Adaptation BenchmarkCode0
Towards detection and classification of microscopic foraminifera using transfer learningCode0
Unsupervised Cross-domain Image Classification by Distance Metric Guided Feature AlignmentCode0
The Utility of Decorrelating Colour Spaces in Vector Quantised Variational AutoencodersCode0
Specifying and Testing k-Safety Properties for Machine-Learning ModelsCode0
What to Do When Your Discrete Optimization Is the Size of a Neural Network?Code0
SgVA-CLIP: Semantic-guided Visual Adapting of Vision-Language Models for Few-shot Image ClassificationCode0
The Unmet Promise of Synthetic Training Images: Using Retrieved Real Images Performs BetterCode0
Visual Representation Learning with Self-Supervised Attention for Low-Label High-data RegimeCode0
The Tsetlin Machine - A Game Theoretic Bandit Driven Approach to Optimal Pattern Recognition with Propositional LogicCode0
Towards Faster Training of Global Covariance Pooling Networks by Iterative Matrix Square Root NormalizationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94Unverified
4DaViT-GTop 1 Accuracy90.4Unverified
5DaViT-HTop 1 Accuracy90.2Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90Unverified