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 22012225 of 10420 papers

TitleStatusHype
Deep Fast Vision: Accelerated Deep Transfer Learning Vision Prototyping and BeyondCode1
Contrastive Masked Autoencoders are Stronger Vision LearnersCode1
Interferometric Graph Transform: a Deep Unsupervised Graph RepresentationCode1
Convolutional Spiking Neural Networks for Spatio-Temporal Feature ExtractionCode1
Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy LabelsCode1
DeepGleason: a System for Automated Gleason Grading of Prostate Cancer using Deep Neural NetworksCode1
InterLUDE: Interactions between Labeled and Unlabeled Data to Enhance Semi-Supervised LearningCode1
Convolutional Xformers for VisionCode1
Convolutional Sequence to Sequence LearningCode1
Integrated Image and Location Analysis for Wound Classification: A Deep Learning ApproachCode1
Instance-Dependent Noisy Label Learning via Graphical ModellingCode1
Deep Learning Based Brain Tumor Segmentation: A SurveyCode1
Instance-Conditional Knowledge Distillation for Object DetectionCode1
Deep-Learning-Based Aerial Image Classification for Emergency Response Applications Using Unmanned Aerial VehiclesCode1
Instance Localization for Self-supervised Detection PretrainingCode1
Masked Autoencoders Are Scalable Vision LearnersCode1
Convolutional Channel-wise Competitive Learning for the Forward-Forward AlgorithmCode1
Curriculum Labeling: Revisiting Pseudo-Labeling for Semi-Supervised LearningCode1
InsPLAD: A Dataset and Benchmark for Power Line Asset Inspection in UAV ImagesCode1
ConvMLP: Hierarchical Convolutional MLPs for VisionCode1
A Survey on Transferability of Adversarial Examples across Deep Neural NetworksCode1
Masked Unsupervised Self-training for Label-free Image ClassificationCode1
Instance Similarity Learning for Unsupervised Feature RepresentationCode1
Interpolation between Residual and Non-Residual NetworksCode1
Introspective Deep Metric Learning for Image RetrievalCode1
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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