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 18011850 of 10419 papers

TitleStatusHype
Anytime Continual Learning for Open Vocabulary ClassificationCode1
Region Comparison Network for Interpretable Few-shot Image ClassificationCode1
Adversarial Continual LearningCode1
Regression Metric Loss: Learning a Semantic Representation Space for Medical ImagesCode1
Regularized Optimal Transport Layers for Generalized Global Pooling OperationsCode1
Regularizing and Optimizing LSTM Language ModelsCode1
A Panda? No, It's a Sloth: Slowdown Attacks on Adaptive Multi-Exit Neural Network InferenceCode1
Cross-Domain Ensemble Distillation for Domain GeneralizationCode1
CrossFormer: A Versatile Vision Transformer Hinging on Cross-scale AttentionCode1
Relative Positional Encoding for Transformers with Linear ComplexityCode1
Deep Prototypical Networks with Hybrid Residual Attention for Hyperspectral Image ClassificationCode1
ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation AnchoringCode1
A Partially Reversible U-Net for Memory-Efficient Volumetric Image SegmentationCode1
Remote Sensing Change Detection With Transformers Trained from ScratchCode1
[Re] Rigging the Lottery: Making All Tickets WinnersCode1
Class-Incremental Grouping Network for Continual Audio-Visual LearningCode1
Reproducible scaling laws for contrastive language-image learningCode1
CLR: Channel-wise Lightweight Reprogramming for Continual LearningCode1
ResMLP: Feedforward networks for image classification with data-efficient trainingCode1
Active Domain Adaptation via Clustering Uncertainty-weighted EmbeddingsCode1
ResNet strikes back: An improved training procedure in timmCode1
ResT: An Efficient Transformer for Visual RecognitionCode1
Clusterability as an Alternative to Anchor Points When Learning with Noisy LabelsCode1
Rethinking Local Perception in Lightweight Vision TransformerCode1
Rethinking model prototyping through the MedMNIST+ dataset collectionCode1
Rethinking Multiple Instance Learning for Whole Slide Image Classification: A Good Instance Classifier is All You NeedCode1
Adversarial Example Detection for DNN Models: A Review and Experimental ComparisonCode1
Rethinking Recurrent Neural Networks and Other Improvements for Image ClassificationCode1
Deep Roto-Translation Scattering for Object ClassificationCode1
Rethinking the Inception Architecture for Computer VisionCode1
Deep Transfer Learning for Land Use and Land Cover Classification: A Comparative StudyCode1
Deep Networks with Stochastic DepthCode1
Reversible Vision TransformersCode1
Revising deep learning methods in parking lot occupancy detectionCode1
Revisiting Discriminative vs. Generative Classifiers: Theory and ImplicationsCode1
Revisiting Label Smoothing and Knowledge Distillation Compatibility: What was Missing?Code1
CLCC: Contrastive Learning for Color ConstancyCode1
CLCNet: Rethinking of Ensemble Modeling with Classification Confidence NetworkCode1
Cross-Layer Retrospective Retrieving via Layer AttentionCode1
Clean-Label Backdoor Attacks on Video Recognition ModelsCode1
CleanNet: Transfer Learning for Scalable Image Classifier Training with Label NoiseCode1
Revisiting Weakly Supervised Pre-Training of Visual Perception ModelsCode1
Adversarial Examples in Deep Learning for Multivariate Time Series RegressionCode1
Revitalizing CNN Attention via Transformers in Self-Supervised Visual Representation LearningCode1
Rethinking Channel Dimensions for Efficient Model DesignCode1
CLIP4IDC: CLIP for Image Difference CaptioningCode1
A Comprehensive Survey on Graph Neural NetworksCode1
A Fuzzy Rank-based Ensemble of CNN Models for Classification of Cervical CytologyCode1
Robotic Pick-and-Place of Novel Objects in Clutter with Multi-Affordance Grasping and Cross-Domain Image MatchingCode1
DeepNoise: Signal and Noise Disentanglement based on Classifying Fluorescent Microscopy Images via Deep LearningCode1
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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
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
6DaViT-HTop 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10RevCol-HTop 1 Accuracy90Unverified