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 76517675 of 10420 papers

TitleStatusHype
E2GC: Energy-efficient Group Convolution in Deep Neural NetworksCode0
4S-DT: Self Supervised Super Sample Decomposition for Transfer learning with application to COVID-19 detection0
A Comparative Analysis on Bangla Handwritten Digit Recognition with Data Augmentation and Non-Augmentation ProcessCode0
Diverse Knowledge Distillation (DKD): A Solution for Improving The Robustness of Ensemble Models Against Adversarial Attacks0
Target Consistency for Domain Adaptation: when Robustness meets Transferability0
Set Based Stochastic Subsampling0
When Do Neural Networks Outperform Kernel Methods?Code0
Learning Interclass Relations for Image Classification0
Interpretable Deep Models for Cardiac Resynchronisation Therapy Response Prediction0
Time for a Background Check! Uncovering the impact of Background Features on Deep Neural Networks0
Ramanujan Bipartite Graph Products for Efficient Block Sparse Neural Networks0
Hyperparameter Ensembles for Robustness and Uncertainty QuantificationCode0
Post-hoc Calibration of Neural Networks by g-Layers0
Effective Version Space Reduction for Convolutional Neural Networks0
Don’t Wait, Just Weight: Improving Unsupervised Representations by Learning Goal-Driven Instance Weights0
Auxiliary Learning by Implicit Differentiation0
RP2K: A Large-Scale Retail Product Dataset for Fine-Grained Image Classification0
MaxVA: Fast Adaptation of Step Sizes by Maximizing Observed Variance of GradientsCode0
Gradient-EM Bayesian Meta-learning0
Unsupervised Image Classification for Deep Representation LearningCode0
Adversarial Transfer of Pose Estimation Regression0
A Bayesian Evaluation Framework for Subjectively Annotated Visual Recognition TasksCode0
Keep Your AI-es on the Road: Tackling Distracted Driver Detection with Convolutional Neural Networks and Targeted Data Augmentation0
Adaptive feature recombination and recalibration for semantic segmentation with Fully Convolutional NetworksCode0
AutoOD: Automated Outlier Detection via Curiosity-guided Search and Self-imitation Learning0
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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