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 15761600 of 10420 papers

TitleStatusHype
Breast Cancer Histopathology Image Classification and Localization using Multiple Instance LearningCode1
Direct Parameterization of Lipschitz-Bounded Deep NetworksCode1
FedIIC: Towards Robust Federated Learning for Class-Imbalanced Medical Image ClassificationCode1
Dirichlet-based Uncertainty Calibration for Active Domain AdaptationCode1
DISC: Learning From Noisy Labels via Dynamic Instance-Specific Selection and CorrectionCode1
On Creating Benchmark Dataset for Aerial Image Interpretation: Reviews, Guidances and Million-AIDCode1
BRECQ: Pushing the Limit of Post-Training Quantization by Block ReconstructionCode1
FedSOL: Stabilized Orthogonal Learning with Proximal Restrictions in Federated LearningCode1
Discretization-Aware Architecture SearchCode1
Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective AdaptationCode1
Multi-Label Learning from Single Positive LabelsCode1
A New Benchmark: On the Utility of Synthetic Data with Blender for Bare Supervised Learning and Downstream Domain AdaptationCode1
Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural NetworksCode1
FedMLP: Federated Multi-Label Medical Image Classification under Task HeterogeneityCode1
Multi-level Multiple Instance Learning with Transformer for Whole Slide Image ClassificationCode1
Reviving the Context: Camera Trap Species Classification as Link Prediction on Multimodal Knowledge GraphsCode1
Discriminator-free Unsupervised Domain Adaptation for Multi-label Image ClassificationCode1
BSNet: Bi-Similarity Network for Few-shot Fine-grained Image ClassificationCode1
BSRBF-KAN: A combination of B-splines and Radial Basis Functions in Kolmogorov-Arnold NetworksCode1
Disentangle and Remerge: Interventional Knowledge Distillation for Few-Shot Object Detection from A Conditional Causal PerspectiveCode1
Multimodal Model-Agnostic Meta-Learning via Task-Aware ModulationCode1
Disentangled Ontology Embedding for Zero-shot LearningCode1
Disentangled Feature Representation for Few-shot Image ClassificationCode1
Cervical Cytology Classification Using PCA & GWO Enhanced Deep Features SelectionCode1
FedProc: Prototypical Contrastive Federated Learning on Non-IID dataCode1
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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