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 20012050 of 10419 papers

TitleStatusHype
Contextual Diversity for Active LearningCode1
Improved Baselines with Momentum Contrastive LearningCode1
Head Network Distillation: Splitting Distilled Deep Neural Networks for Resource-Constrained Edge Computing SystemsCode1
Heteroskedastic and Imbalanced Deep Learning with Adaptive RegularizationCode1
Heavy Ball Neural Ordinary Differential EquationsCode1
Towards Accurate and Interpretable Neuroblastoma Diagnosis via Contrastive Multi-scale Pathological Image AnalysisCode1
A Robust Feature Downsampling Module for Remote Sensing Visual TasksCode1
Hidden Trigger Backdoor AttacksCode1
Heuristic Hyperparameter Optimization for Convolutional Neural Networks using Genetic AlgorithmCode1
Improved Regularization and Robustness for Fine-tuning in Neural NetworksCode1
Complementary-Label Learning for Arbitrary Losses and ModelsCode1
Towards Effective Visual Representations for Partial-Label LearningCode1
Hierarchical Image Classification using Entailment Cone EmbeddingsCode1
Towards Evaluating Explanations of Vision Transformers for Medical ImagingCode1
A Fast Knowledge Distillation Framework for Visual RecognitionCode1
Hire-MLP: Vision MLP via Hierarchical RearrangementCode1
High-Performance Large-Scale Image Recognition Without NormalizationCode1
HVT: A Comprehensive Vision Framework for Learning in Non-Euclidean SpaceCode1
Counterfactual Explanations for Medical Image Classification and Regression using Diffusion AutoencoderCode1
Towards Label-free Scene Understanding by Vision Foundation ModelsCode1
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustnessCode1
Towards Open-Set Test-Time Adaptation Utilizing the Wisdom of Crowds in Entropy MinimizationCode1
ACPL: Anti-curriculum Pseudo-labelling for Semi-supervised Medical Image ClassificationCode1
Histopathological Image Classification with Cell Morphology Aware Deep Neural NetworksCode1
Hit-Detector: Hierarchical Trinity Architecture Search for Object DetectionCode1
HMIL: Hierarchical Multi-Instance Learning for Fine-Grained Whole Slide Image ClassificationCode1
Consistency-based Active Learning for Object DetectionCode1
Image Representations Learned With Unsupervised Pre-Training Contain Human-like BiasesCode1
How Does Pruning Impact Long-Tailed Multi-Label Medical Image Classifiers?Code1
Towards Uncovering the Intrinsic Data Structures for Unsupervised Domain Adaptation using Structurally Regularized Deep ClusteringCode1
How to Learn More? Exploring Kolmogorov-Arnold Networks for Hyperspectral Image ClassificationCode1
Shallow-Deep Networks: Understanding and Mitigating Network OverthinkingCode1
ImageNet-21K Pretraining for the MassesCode1
Image-free Classifier Injection for Zero-Shot ClassificationCode1
How to train your ViT? Data, Augmentation, and Regularization in Vision TransformersCode1
Trainable Noise Model as an XAI evaluation method: application on Sobol for remote sensing image segmentationCode1
Stateful ODE-Nets using Basis Function ExpansionsCode1
Compressing Features for Learning with Noisy LabelsCode1
A Second-Order Approach to Learning with Instance-Dependent Label NoiseCode1
HRFormer: High-Resolution Transformer for Dense PredictionCode1
HR-NAS: Searching Efficient High-Resolution Neural Architectures with Lightweight TransformersCode1
HRN: A Holistic Approach to One Class LearningCode1
Training on Thin Air: Improve Image Classification with Generated DataCode1
Compressive Visual RepresentationsCode1
ImageNet Large Scale Visual Recognition ChallengeCode1
HS-ResNet: Hierarchical-Split Block on Convolutional Neural NetworkCode1
Image sensing with multilayer, nonlinear optical neural networksCode1
Image Classification with Small Datasets: Overview and BenchmarkCode1
Conformer: Local Features Coupling Global Representations for Visual RecognitionCode1
Image Clustering with External GuidanceCode1
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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