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 7851–7900 of 10420 papers

TitleStatusHype
Benchmarking Adversarial Robustness—0
Competing Ratio Loss for Discriminative Multi-class Image ClassificationCode0
Effective Data Augmentation with Multi-Domain Learning GANs—0
Learn to Segment Retinal Lesions and BeyondCode0
An Analysis of the Expressiveness of Deep Neural Network Architectures Based on Their Lipschitz Constants—0
Adversarial AutoAugment—0
Big Transfer (BiT): General Visual Representation LearningCode2
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 Representations—0
Image Analytics for Legal Document Review: A Transfer Learning Approach—0
Towards Verifying Robustness of Neural Networks Against Semantic PerturbationsCode0
A New Ensemble Method for Concessively Targeted Multi-model Attack—0
Overcoming Long-term Catastrophic Forgetting through Adversarial Neural Pruning and Synaptic ConsolidationCode0
Making Better Mistakes: Leveraging Class Hierarchies with Deep NetworksCode0
ResNetX: a more disordered and deeper network architecture—0
Invariant Attribute Profiles: A Spatial-Frequency Joint Feature Extractor for Hyperspectral Image Classification—0
Continuous Meta-Learning without TasksCode0
Semantic Regularization: Improve Few-shot Image Classification by Reducing Meta Shift—0
A Web Page Classifier Library Based on Random Image Content Analysis Using Deep Learning—0
Direction Concentration Learning: Enhancing Congruency in Machine LearningCode0
Cross-Modality Attention with Semantic Graph Embedding for Multi-Label Classification—0
PolSF: PolSAR image dataset on San FranciscoCode1
Transductive Zero-Shot Learning for 3D Point Cloud ClassificationCode1
Disentanglement based Active LearningCode0
Deep Poisoning: Towards Robust Image Data Sharing against Visual Disclosure—0
Meta-Learning Initializations for Image SegmentationCode0
TopoAct: Visually Exploring the Shape of Activations in Deep LearningCode0
Recurrent Highway Networks with Grouped Auxiliary MemoryCode0
Towards Partial Supervision for Generic Object Counting in Natural ScenesCode0
Row-Sparse Discriminative Deep Dictionary Learning for Hyperspectral Image Classification—0
Discriminative Robust Deep Dictionary Learning for Hyperspectral Image Classification—0
Label Consistent Transform Learning for Hyperspectral Image Classification—0
Parting with Illusions about Deep Active Learning—0
Wide-Area Land Cover Mapping with Sentinel-1 Imagery using Deep Learning Semantic Segmentation Models—0
Image Classification with Deep Learning in the Presence of Noisy Labels: A SurveyCode1
Associative Alignment for Few-shot Image ClassificationCode0
Scalable Fine-grained Generated Image Classification Based on Deep Metric Learning—0
Feature Losses for Adversarial Robustness—0
Arithmetic addition of two integers by deep image classification networks: experiments to quantify their autonomous reasoning abilityCode0
Appending Adversarial Frames for Universal Video Attack—0
SpineNet: Learning Scale-Permuted Backbone for Recognition and LocalizationCode0
Deep Adaptive Wavelet NetworkCode0
Naive Gabor Networks for Hyperspectral Image Classification—0
Meta-Learning without MemorizationCode0
Selective Synthetic Augmentation with Quality Assurance—0
Learning Disentangled Representations via Mutual Information EstimationCode0
Principal Component Properties of Adversarial Samples—0
Dynamic Convolution: Attention over Convolution KernelsCode0
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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
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2—Unverified
6DaViT-HTop 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
10RevCol-HTop 1 Accuracy90—Unverified