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

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Showing 7551–7575 of 10420 papers

TitleStatusHype
Out-of-distribution Generalization via Partial Feature Decorrelation—0
Learning from Few Samples: A Survey—0
Deep learning for lithological classification of carbonate rock micro-CT images—0
Growing Efficient Deep Networks by Structured Continuous Sparsification—0
flexgrid2vec: Learning Efficient Visual Representations Vectors—0
Demystifying Contrastive Self-Supervised Learning: Invariances, Augmentations and Dataset Biases—0
Rethinking Generative Zero-Shot Learning: An Ensemble Learning Perspective for Recognising Visual Patches—0
Towards Learning Convolutions from ScratchCode0
Semi-Supervised Learning with Data Augmentation for End-to-End ASR—0
Reconstruction Regularized Deep Metric Learning for Multi-label Image Classification—0
Towards Accuracy-Fairness Paradox: Adversarial Example-based Data Augmentation for Visual Debiasing—0
Contraction Mapping of Feature Norms for Classifier Learning on the Data with Different Quality—0
Train Like a (Var)Pro: Efficient Training of Neural Networks with Variable ProjectionCode0
Neural networks with late-phase weightsCode0
All-Optical Information Processing Capacity of Diffractive Surfaces—0
T-BFA: Targeted Bit-Flip Adversarial Weight AttackCode0
Hallucinating Saliency Maps for Fine-Grained Image Classification for Limited Data Domains—0
Right for the Right Reason: Making Image Classification Robust—0
Complementing Representation Deficiency in Few-shot Image Classification: A Meta-Learning ApproachCode0
Multi-label Thoracic Disease Image Classification with Cross-Attention Networks—0
GREEN: a Graph REsidual rE-ranking Network for Grading Diabetic RetinopathyCode0
Survey on Deep Learning-based Kuzushiji Recognition—0
A Bag of Visual Words Model for Medical Image Retrieval—0
MIX'EM: Unsupervised Image Classification using a Mixture of Embeddings—0
Robust Image Classification Using A Low-Pass Activation Function and DCT AugmentationCode0
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All datasetsImageNetCIFAR-10CIFAR-100STL-10ObjectNetMNISTSVHNiNaturalist 2018ImageNet ReaLFlowers-102Clothing1Mmini WebVision 1.0

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91—Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98—Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94—Unverified
4DaViT-GTop 1 Accuracy90.4—Unverified
5DaViT-HTop 1 Accuracy90.2—Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2—Unverified
7SwinV2-GTop 1 Accuracy90.17—Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1—Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05—Unverified
10RevCol-HTop 1 Accuracy90—Unverified