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 476500 of 10419 papers

TitleStatusHype
Content-aware Token Sharing for Efficient Semantic Segmentation with Vision TransformersCode1
Contextual Convolutional Neural NetworksCode1
AutoDC: Automated data-centric processingCode1
Can We Talk Models Into Seeing the World Differently?Code1
3D Human Pose Estimation with Spatial and Temporal TransformersCode1
A Contrastive Distillation Approach for Incremental Semantic Segmentation in Aerial ImagesCode1
DeBiFormer: Vision Transformer with Deformable Agent Bi-level Routing AttentionCode1
AutoLRS: Automatic Learning-Rate Schedule by Bayesian Optimization on the FlyCode1
Auto Learning AttentionCode1
Automated detection of COVID-19 cases from chest X-ray images using deep neural network and XGBoostCode1
Automated Learning Rate Scheduler for Large-batch TrainingCode1
Automatically designing CNN architectures using genetic algorithm for image classificationCode1
Decoupled Weight Decay RegularizationCode1
Deep AutoAugmentCode1
Container: Context Aggregation NetworkCode1
Automatic Recognition of Abdominal Organs in Ultrasound Images based on Deep Neural Networks and K-Nearest-Neighbor ClassificationCode1
Deep convolutional tensor networkCode1
DeepEMD: Differentiable Earth Mover's Distance for Few-Shot LearningCode1
Deep Factorized Metric LearningCode1
Spatial and Spatial-Spectral Morphological Mamba for Hyperspectral Image ClassificationCode1
AutoMix: Unveiling the Power of Mixup for Stronger ClassifiersCode1
Contextual Diversity for Active LearningCode1
A Fast 3D CNN for Hyperspectral Image ClassificationCode1
AutoSpeech: Neural Architecture Search for Speaker RecognitionCode1
Confidence Regularized Self-TrainingCode1
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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