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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 9101–9125 of 10420 papers

TitleStatusHype
Face Identification with Second-Order Pooling—0
Face Image Classification by Pooling Raw Features—0
FACET: Fairness in Computer Vision Evaluation Benchmark—0
Fact or Artifact? Revise Layer-wise Relevance Propagation on various ANN Architectures—0
Factorized Adversarial Networks for Unsupervised Domain Adaptation—0
Factors of Influence for Transfer Learning across Diverse Appearance Domains and Task Types—0
FACTUAL: A Novel Framework for Contrastive Learning Based Robust SAR Image Classification—0
Failure Prediction by Confidence Estimation of Uncertainty-Aware Dirichlet Networks—0
Fair Comparison: Quantifying Variance in Resultsfor Fine-grained Visual Categorization—0
FairDD: Fair Dataset Distillation via Synchronized Matching—0
Fair Distillation: Teaching Fairness from Biased Teachers in Medical Imaging—0
Fairness Analysis of CLIP-Based Foundation Models for X-Ray Image Classification—0
Fairness-Aware Meta-Learning via Nash Bargaining—0
Fairness Testing of Deep Image Classification with Adequacy Metrics—0
FairPrune: Achieving Fairness Through Pruning for Dermatological Disease Diagnosis—0
FairREAD: Re-fusing Demographic Attributes after Disentanglement for Fair Medical Image Classification—0
FairSAM: Fair Classification on Corrupted Data Through Sharpness-Aware Minimization—0
Fair-VPT: Fair Visual Prompt Tuning for Image Classification—0
FALIP: Visual Prompt as Foveal Attention Boosts CLIP Zero-Shot Performance—0
Fall Leaf Adversarial Attack on Traffic Sign Classification—0
Fantope Regularization in Metric Learning—0
Fashion and Apparel Classification using Convolutional Neural Networks—0
Fashion CUT: Unsupervised domain adaptation for visual pattern classification in clothes using synthetic data and pseudo-labels—0
FastAdaBelief: Improving Convergence Rate for Belief-based Adaptive Optimizers by Exploiting Strong Convexity—0
Fast Adaptation with Bradley-Terry Preference Models in Text-To-Image Classification and Generation—0
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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
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified