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 19762000 of 10420 papers

TitleStatusHype
SVFormer: Semi-supervised Video Transformer for Action RecognitionCode1
SWIFT: Rapid Decentralized Federated Learning via Wait-Free Model CommunicationCode1
Densely Connected Convolutional NetworksCode1
Deep convolutional tensor networkCode1
Synthesis of COVID-19 Chest X-rays using Unpaired Image-to-Image TranslationCode1
Can We Talk Models Into Seeing the World Differently?Code1
Beyond Synthetic Noise: Deep Learning on Controlled Noisy LabelsCode1
Dense Contrastive Learning for Self-Supervised Visual Pre-TrainingCode1
Deep Factorized Metric LearningCode1
Targeted Visualization of the Backbone of Encoder LLMsCode1
Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained ModelsCode1
Task-Oriented Feature DistillationCode1
Dendritic Learning-incorporated Vision Transformer for Image RecognitionCode1
DenoiseRep: Denoising Model for Representation LearningCode1
TCJA-SNN: Temporal-Channel Joint Attention for Spiking Neural NetworksCode1
Depth Uncertainty in Neural NetworksCode1
Detecting AutoAttack Perturbations in the Frequency DomainCode1
Tensor Networks for Medical Image ClassificationCode1
Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge DistillationCode1
A Fast 3D CNN for Hyperspectral Image ClassificationCode1
Test-time Adaptation with Calibration of Medical Image Classification Nets for Label Distribution ShiftCode1
Delta-STN: Efficient Bilevel Optimization for Neural Networks using Structured Response JacobiansCode1
Text Classification in Memristor-based Spiking Neural NetworksCode1
The Cascaded Forward Algorithm for Neural Network TrainingCode1
DeiT-LT Distillation Strikes Back for Vision Transformer Training on Long-Tailed DatasetsCode1
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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