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 851860 of 10420 papers

TitleStatusHype
Evaluating the visualization of what a Deep Neural Network has learnedCode1
Evaluation of Deep Neural Network Domain Adaptation Techniques for Image RecognitionCode1
AdvCLIP: Downstream-agnostic Adversarial Examples in Multimodal Contrastive LearningCode1
EViT: An Eagle Vision Transformer with Bi-Fovea Self-AttentionCode1
Evo-ViT: Slow-Fast Token Evolution for Dynamic Vision TransformerCode1
EXACT: How to Train Your AccuracyCode1
Expediting Large-Scale Vision Transformer for Dense Prediction without Fine-tuningCode1
Explainable Convolutional Neural Networks for Retinal Fundus Classification and Cutting-Edge Segmentation Models for Retinal Blood Vessels from Fundus ImagesCode1
A Comprehensive Approach to Unsupervised Embedding Learning based on AND AlgorithmCode1
CLIP the Gap: A Single Domain Generalization Approach for Object DetectionCode1
Show:102550
← PrevPage 86 of 1042Next →

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