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 80518075 of 10420 papers

TitleStatusHype
SESS: Self-Ensembling Semi-Supervised 3D Object DetectionCode0
Competing Ratio Loss for Discriminative Multi-class Image ClassificationCode0
Effective Data Augmentation with Multi-Domain Learning GANs0
Learn to Segment Retinal Lesions and BeyondCode0
Adversarial AutoAugment0
An Analysis of the Expressiveness of Deep Neural Network Architectures Based on Their Lipschitz Constants0
Deep Manifold Embedding for Hyperspectral Image ClassificationCode0
A Deep Neuro-Fuzzy Network for Image ClassificationCode0
Learning to Impute: A General Framework for Semi-supervised LearningCode0
Multimodal Prediction based on Graph Representations0
Overcoming Long-term Catastrophic Forgetting through Adversarial Neural Pruning and Synaptic ConsolidationCode0
A New Ensemble Method for Concessively Targeted Multi-model Attack0
Making Better Mistakes: Leveraging Class Hierarchies with Deep NetworksCode0
Image Analytics for Legal Document Review: A Transfer Learning Approach0
Towards Verifying Robustness of Neural Networks Against Semantic PerturbationsCode0
ResNetX: a more disordered and deeper network architecture0
Semantic Regularization: Improve Few-shot Image Classification by Reducing Meta Shift0
Invariant Attribute Profiles: A Spatial-Frequency Joint Feature Extractor for Hyperspectral Image Classification0
A Web Page Classifier Library Based on Random Image Content Analysis Using Deep Learning0
Continuous Meta-Learning without TasksCode0
Direction Concentration Learning: Enhancing Congruency in Machine LearningCode0
Cross-Modality Attention with Semantic Graph Embedding for Multi-Label Classification0
Disentanglement based Active LearningCode0
Deep Poisoning: Towards Robust Image Data Sharing against Visual Disclosure0
Recurrent Highway Networks with Grouped Auxiliary MemoryCode0
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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