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 97769800 of 10420 papers

TitleStatusHype
Deep Active Learning with Augmentation-based Consistency EstimationCode0
BEiT v2: Masked Image Modeling with Vector-Quantized Visual TokenizersCode0
Privacy Enhancement for Cloud-Based Few-Shot LearningCode0
Learning rotation invariant convolutional filters for texture classificationCode0
Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty and Adversarial RobustnessCode0
Learning Self-Supervised Representations for Label Efficient Cross-Domain Knowledge Transfer on Diabetic Retinopathy Fundus ImagesCode0
DED: Diagnostic Evidence Distillation for acne severity grading on face imagesCode0
Decoupled Greedy Learning of CNNsCode0
Rationally Inattentive Utility Maximization for Interpretable Deep Image ClassificationCode0
No Wrong Turns: The Simple Geometry Of Neural Networks Optimization PathsCode0
Adversarial Defense by Suppressing High-frequency ComponentsCode0
Learning Sparse & Ternary Neural Networks with Entropy-Constrained Trained Ternarization (EC2T)Code0
Learning Spatial Regularization with Image-level Supervisions for Multi-label Image ClassificationCode0
Decompose-and-Compose: A Compositional Approach to Mitigating Spurious CorrelationCode0
Adversarial Augmentation for Enhancing Classification of Mammography ImagesCode0
BDNet: Bengali Handwritten Numeral Digit Recognition based on Densely connected Convolutional Neural NetworksCode0
BayTTA: Uncertainty-aware medical image classification with optimized test-time augmentation using Bayesian model averagingCode0
Bayesian Robust Aggregation for Federated LearningCode0
Decoding visual brain representations from electroencephalography through Knowledge Distillation and latent diffusion modelsCode0
Learning Symmetrization for Equivariance with Orbit Distance MinimizationCode0
BSDA: Bayesian Random Semantic Data Augmentation for Medical Image ClassificationCode0
NUAA-QMUL at SemEval-2020 Task 8: Utilizing BERT and DenseNet for Internet Meme Emotion AnalysisCode0
Tensor Train Factorization and Completion under Noisy Data with Prior Analysis and Rank EstimationCode0
Null-sampling for Interpretable and Fair RepresentationsCode0
Learning the Prediction Distribution for Semi-Supervised Learning with Normalising FlowsCode0
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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
5DaViT-HTop 1 Accuracy90.2Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90Unverified