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 1951–2000 of 10419 papers

TitleStatusHype
Combining Metric Learning and Attention Heads For Accurate and Efficient Multilabel Image ClassificationCode1
Are Natural Domain Foundation Models Useful for Medical Image Classification?Code1
Split Computing and Early Exiting for Deep Learning Applications: Survey and Research ChallengesCode1
Split Computing for Complex Object Detectors: Challenges and Preliminary ResultsCode1
SP-ViT: Learning 2D Spatial Priors for Vision TransformersCode1
Squeeze-and-Excitation NetworksCode1
DetCo: Unsupervised Contrastive Learning for Object DetectionCode1
SS-MAE: Spatial-Spectral Masked Auto-Encoder for Multi-Source Remote Sensing Image ClassificationCode1
Deep Complex NetworksCode1
Complementary-Label Learning for Arbitrary Losses and ModelsCode1
Stereopagnosia: Fooling Stereo Networks with Adversarial PerturbationsCode1
A Spectral-Spatial-Dependent Global Learning Framework for Insufficient and Imbalanced Hyperspectral Image ClassificationCode1
Stochastic Layer-Wise Shuffle: A Good Practice to Improve Vision Mamba TrainingCode1
Stochastic-YOLO: Efficient Probabilistic Object Detection under Dataset ShiftsCode1
Are These Birds Similar: Learning Branched Networks for Fine-grained RepresentationsCode1
One Explanation is Not Enough: Structured Attention Graphs for Image ClassificationCode1
Communication-Efficient and Privacy-Preserving Feature-based Federated Transfer LearningCode1
Style-Hallucinated Dual Consistency Learning: A Unified Framework for Visual Domain GeneralizationCode1
Subspace Regularizers for Few-Shot Class Incremental LearningCode1
Communication-Efficient Federated Learning Based on Explanation-Guided Pruning for Remote Sensing Image ClassificationCode1
Depth-Wise Convolutions in Vision Transformers for Efficient Training on Small DatasetsCode1
A General Framework For Detecting Anomalous Inputs to DNN ClassifiersCode1
Supervised Dimensionality Reduction and Image Classification Utilizing Convolutional AutoencodersCode1
Supporting large-scale image recognition with out-of-domain samplesCode1
Deep CORAL: Correlation Alignment for Deep Domain AdaptationCode1
SVFormer: Semi-supervised Video Transformer for Action RecognitionCode1
SWIFT: Rapid Decentralized Federated Learning via Wait-Free Model CommunicationCode1
Densely Connected Convolutional NetworksCode1
Deep convolutional tensor networkCode1
Synthesis of COVID-19 Chest X-rays using Unpaired Image-to-Image TranslationCode1
Can We Talk Models Into Seeing the World Differently?Code1
Beyond Synthetic Noise: Deep Learning on Controlled Noisy LabelsCode1
Dense Contrastive Learning for Self-Supervised Visual Pre-TrainingCode1
Deep Factorized Metric LearningCode1
Targeted Visualization of the Backbone of Encoder LLMsCode1
Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained ModelsCode1
Task-Oriented Feature DistillationCode1
Dendritic Learning-incorporated Vision Transformer for Image RecognitionCode1
DenoiseRep: Denoising Model for Representation LearningCode1
TCJA-SNN: Temporal-Channel Joint Attention for Spiking Neural NetworksCode1
Depth Uncertainty in Neural NetworksCode1
Detecting AutoAttack Perturbations in the Frequency DomainCode1
Tensor Networks for Medical Image ClassificationCode1
Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge DistillationCode1
A Fast 3D CNN for Hyperspectral Image ClassificationCode1
Test-time Adaptation with Calibration of Medical Image Classification Nets for Label Distribution ShiftCode1
Delta-STN: Efficient Bilevel Optimization for Neural Networks using Structured Response JacobiansCode1
Text Classification in Memristor-based Spiking Neural NetworksCode1
The Cascaded Forward Algorithm for Neural Network TrainingCode1
DeiT-LT Distillation Strikes Back for Vision Transformer Training on Long-Tailed DatasetsCode1
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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
5DaViT-HTop 1 Accuracy90.2—Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 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
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified