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 41264150 of 10420 papers

TitleStatusHype
Attend and Guide (AG-Net): A Keypoints-driven Attention-based Deep Network for Image RecognitionCode0
Hyperspectral Image Classification in the Presence of Noisy LabelsCode0
Coupling Adaptive Batch Sizes with Learning RatesCode0
Hyperspectral Image Classification: Artifacts of Dimension Reduction on Hybrid CNNCode0
Couplformer:Rethinking Vision Transformer with Coupling Attention MapCode0
Hyperparameter Ensembles for Robustness and Uncertainty QuantificationCode0
Hyper-Process Model: A Zero-Shot Learning algorithm for Regression Problems based on Shape AnalysisCode0
Countering Adversarial Images using Input TransformationsCode0
Counterfactual Reasoning for Multi-Label Image Classification via Patching-Based TrainingCode0
Deeply-supervised Knowledge SynergyCode0
Hyperbolic Sliced-Wasserstein via Geodesic and Horospherical ProjectionsCode0
HyperDID: Hyperspectral Intrinsic Image Decomposition with Deep Feature EmbeddingCode0
Hyperspectral Image Classification With Contrastive Graph Convolutional NetworkCode0
Counterfactual Explanation and Instance-Generation using Cycle-Consistent Generative Adversarial NetworksCode0
A Transformer Framework for Data Fusion and Multi-Task Learning in Smart CitiesCode0
A Transfer Learning and Explainable Solution to Detect mpox from Smartphones imagesCode0
A Training Framework for Optimal and Stable Training of Polynomial Neural NetworksCode0
HybridSN: Exploring 3D-2D CNN Feature Hierarchy for Hyperspectral Image ClassificationCode0
Co-Teaching for Unsupervised Domain Adaptation and ExpansionCode0
A trainable monogenic ConvNet layer robust in front of large contrast changes in image classificationCode0
A Hierarchical Grocery Store Image Dataset with Visual and Semantic LabelsCode0
HyenaPixel: Global Image Context with ConvolutionsCode0
Drop Clause: Enhancing Performance, Interpretability and Robustness of the Tsetlin MachineCode0
Cost-Effective Active Learning for Deep Image ClassificationCode0
Human-in-the-Loop Visual Re-ID for Population Size EstimationCode0
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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