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 601610 of 10419 papers

TitleStatusHype
Adaptive Risk Minimization: Learning to Adapt to Domain ShiftCode1
Clusterability as an Alternative to Anchor Points When Learning with Noisy LabelsCode1
ClusterFormer: Clustering As A Universal Visual LearnerCode1
Co^2L: Contrastive Continual LearningCode1
Achieving Fairness Through Channel Pruning for Dermatological Disease DiagnosisCode1
CLR: Channel-wise Lightweight Reprogramming for Continual LearningCode1
CLIP the Gap: A Single Domain Generalization Approach for Object DetectionCode1
FocusNet: Classifying Better by Focusing on Confusing ClassesCode1
Co2L: Contrastive Continual LearningCode1
CLIP meets DINO for Tuning Zero-Shot Classifier using Unlabeled Image CollectionsCode1
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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