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 1017610200 of 10420 papers

TitleStatusHype
Batch Normalization: Accelerating Deep Network Training byReducing Internal Covariate Shift0
Recipe recognition with large multimodal food datasetCode0
Polarimetric Hierarchical Semantic Model and Scattering Mechanism Based PolSAR Image Classification0
Summarization of Multi-Document Topic Hierarchies using Submodular Mixtures0
Learning to Detect Blue-white Structures in Dermoscopy Images with Weak Supervision0
Online Learning to Sample0
Network Representation Learning with Rich Text InformationCode0
Histopathological Image Classification using Discriminative Feature-oriented Dictionary LearningCode0
Multi-path Convolutional Neural Networks for Complex Image ClassificationCode0
On-the-Job Learning with Bayesian Decision TheoryCode0
Stacked What-Where Auto-encodersCode0
SVM and ELM: Who Wins? Object Recognition with Deep Convolutional Features from ImageNet0
Hyperspectral Image Classification and Clutter Detection via Multiple Structural Embeddings and Dimension Reductions0
Hyper-Class Augmented and Regularized Deep Learning for Fine-Grained Image Classification0
From Dictionary of Visual Words to Subspaces: Locality-Constrained Affine Subspace Coding0
DevNet: A Deep Event Network for Multimedia Event Detection and Evidence Recounting0
Deep Multiple Instance Learning for Image Classification and Auto-Annotation0
Saliency Detection by Multi-Context Deep Learning0
Learning From Massive Noisy Labeled Data for Image Classification0
Modeling Local and Global Deformations in Deep Learning: Epitomic Convolution, Multiple Instance Learning, and Sliding Window Detection0
Learning Graph Structure for Multi-Label Image Classification via Clique Generation0
From Categories to Subcategories: Large-Scale Image Classification With Partial Class Label Refinement0
Exemplar SVMs as Visual Feature Encoders0
Three Viewpoints Toward Exemplar SVM0
Transformation-Invariant Convolutional Jungles0
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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
10RevCol-HTop 1 Accuracy90Unverified