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 44514475 of 10420 papers

TitleStatusHype
When does dough become a bagel? Analyzing the remaining mistakes on ImageNetCode1
Introspective Deep Metric Learning for Image RetrievalCode1
SmoothNets: Optimizing CNN architecture design for differentially private deep learningCode0
VPN: Verification of Poisoning in Neural Networks0
Preservation of High Frequency Content for Deep Learning-Based Medical Image ClassificationCode0
CCMB: A Large-scale Chinese Cross-modal BenchmarkCode1
ConvMAE: Masked Convolution Meets Masked AutoencodersCode2
Comparison Knowledge Translation for Generalizable Image ClassificationCode0
RCMNet: A deep learning model assists CAR-T therapy for leukemia0
Investigating and Explaining the Frequency Bias in Image ClassificationCode1
All Grains, One Scheme (AGOS): Learning Multi-grain Instance Representation for Aerial Scene ClassificationCode0
Large Scale Transfer Learning for Differentially Private Image Classification0
Image Classification With Small Datasets: Overview and BenchmarkCode1
Biologically inspired deep residual networks for computer vision applications0
CoCa: Contrastive Captioners are Image-Text Foundation ModelsCode1
Scene Clustering Based Pseudo-labeling Strategy for Multi-modal Aerial View Object ClassificationCode0
Immiscible Color Flows in Optimal Transport Networks for Image ClassificationCode0
Sequencer: Deep LSTM for Image ClassificationCode5
Masked Generative DistillationCode2
Better plain ViT baselines for ImageNet-1kCode1
Data Determines Distributional Robustness in Contrastive Language Image Pre-training (CLIP)Code1
MIRST-DM: Multi-Instance RST with Drop-Max Layer for Robust Classification of Breast Cancer0
On the generalization capabilities of FSL methods through domain adaptation: a case study in endoscopic kidney stone image classification0
DeepGraviLens: a Multi-Modal Architecture for Classifying Gravitational Lensing DataCode0
Deep PCB To COCO ConvertorCode2
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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
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