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 17511775 of 10419 papers

TitleStatusHype
A Novel lightweight Convolutional Neural Network, ExquisiteNetV2Code1
PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight ImportanceCode1
A Stitch in Time Saves Nine: A Train-Time Regularizing Loss for Improved Neural Network CalibrationCode1
PMatch: Paired Masked Image Modeling for Dense Geometric MatchingCode1
PØDA: Prompt-driven Zero-shot Domain AdaptationCode1
PODA: Prompt-driven Zero-shot Domain AdaptationCode1
PolSF: PolSAR image dataset on San FranciscoCode1
PolyLoss: A Polynomial Expansion Perspective of Classification Loss FunctionsCode1
Age Estimation Using Expectation of Label Distribution LearningCode1
Convolutional Channel-wise Competitive Learning for the Forward-Forward AlgorithmCode1
Circumventing Outliers of AutoAugment with Knowledge DistillationCode1
Deep Learning Based Brain Tumor Segmentation: A SurveyCode1
Predict then Interpolate: A Simple Algorithm to Learn Stable ClassifiersCode1
Predify: Augmenting deep neural networks with brain-inspired predictive coding dynamicsCode1
Building Universal Foundation Models for Medical Image Analysis with Spatially Adaptive NetworksCode1
Pretrained ViTs Yield Versatile Representations For Medical ImagesCode1
Class Adaptive Network CalibrationCode1
ProAPO: Progressively Automatic Prompt Optimization for Visual ClassificationCode1
ProbAct: A Probabilistic Activation Function for Deep Neural NetworksCode1
Class-Aware Contrastive Semi-Supervised LearningCode1
Deep Hyperspectral Unmixing using Transformer NetworkCode1
Class-Balanced Active Learning for Image ClassificationCode1
Class-Balanced Distillation for Long-Tailed Visual RecognitionCode1
Class-Balanced Loss Based on Effective Number of SamplesCode1
LR-Net: A Block-based Convolutional Neural Network for Low-Resolution Image ClassificationCode1
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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