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

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Showing 5901–5950 of 10420 papers

TitleStatusHype
Less is More: Pay Less Attention in Vision TransformersCode1
FoveaTer: Foveated Transformer for Image Classification—0
A Spectral-Spatial-Dependent Global Learning Framework for Insufficient and Imbalanced Hyperspectral Image ClassificationCode1
EDDA: Explanation-driven Data Augmentation to Improve Explanation Faithfulness—0
ResT: An Efficient Transformer for Visual RecognitionCode1
AutoSampling: Search for Effective Data Sampling Schedules—0
A systematic review of transfer learning based approaches for diabetic retinopathy detection—0
Learning Structures for Deep Neural Networks—0
Training With Data Dependent Dynamic Learning Rates—0
Training Classifiers that are Universally Robust to All Label Noise LevelsCode0
Hamiltonian Deep Neural Networks Guaranteeing Non-vanishing Gradients by DesignCode1
Encoders and Ensembles for Task-Free Continual Learning—0
Drawing Multiple Augmentation Samples Per Image During Training Efficiently Decreases Test Error—0
Dynamic Probabilistic Pruning: A general framework for hardware-constrained pruning at different granularities—0
Predict then Interpolate: A Simple Algorithm to Learn Stable ClassifiersCode1
Nested Hierarchical Transformer: Towards Accurate, Data-Efficient and Interpretable Visual UnderstandingCode1
ViPTT-Net: Video pretraining of spatio-temporal model for tuberculosis type classification from chest CT scansCode0
Semi-supervised learning of images with strong rotational disorder: assembling nanoparticle librariesCode0
FedScale: Benchmarking Model and System Performance of Federated Learning at ScaleCode1
Improved OOD Generalization via Adversarial Training and Pre-training—0
Pulmonary embolism identification in computerized tomography pulmonary angiography scans with deep learning technologies in COVID-19 patients—0
StructuralLM: Structural Pre-training for Form Understanding—0
AutoLRS: Automatic Learning-Rate Schedule by Bayesian Optimization on the FlyCode1
PLM: Partial Label Masking for Imbalanced Multi-label Classification—0
ActCooLR – High-Level Learning Rate Schedules using Activation Pattern Temperature—0
Combining Recurrent, Convolutional, and Continuous-time Models with Linear State Space Layers—0
The Regularizing Effect of Different Output Layer Designs in Deep Neural Networks—0
Compressing Deep CNNs using Basis Representation and Spectral Fine-tuningCode0
Extremely Lightweight Quantization Robust Real-Time Single-Image Super Resolution for Mobile DevicesCode1
Safety Metrics for Semantic Segmentation in Autonomous Driving—0
TestRank: Bringing Order into Unlabeled Test Instances for Deep Learning Tasks—0
Anomaly Detection of Adversarial Examples using Class-conditional Generative Adversarial NetworksCode0
Rotation invariant CNN using scattering transform for image classification—0
Visual representation of negation: Real world data analysis on comic image design—0
Opening Deep Neural Networks with Generative ModelsCode0
AnaXNet: Anatomy Aware Multi-label Finding Classification in Chest X-ray—0
Superpixel-based Knowledge Infusion in Deep Neural Networks for Image ClassificationCode1
Intra-Model Collaborative Learning of Neural Networks—0
Correlated Input-Dependent Label Noise in Large-Scale Image Classification—0
Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge DistillationCode1
A Novel lightweight Convolutional Neural Network, ExquisiteNetV2Code1
A Lightweight Privacy-Preserving Scheme Using Label-based Pixel Block Mixing for Image Classification in Deep LearningCode0
Prototype Guided Federated Learning of Visual Feature Representations—0
Accelerating Gossip SGD with Periodic Global Averaging—0
Relative Positional Encoding for Transformers with Linear ComplexityCode1
Sparse Spiking Gradient DescentCode1
Inplace knowledge distillation with teacher assistant for improved training of flexible deep neural networks—0
Deep Metric Learning for Few-Shot Image Classification: A Review of Recent Developments—0
Pay Attention to MLPsCode1
BigEarthNet-MM: A Large Scale Multi-Modal Multi-Label Benchmark Archive for Remote Sensing Image Classification and Retrieval—0
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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