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 451475 of 10419 papers

TitleStatusHype
Controllable Orthogonalization in Training DNNsCode1
Clean-Label Backdoor Attacks on Video Recognition ModelsCode1
Convolutional Channel-wise Competitive Learning for the Forward-Forward AlgorithmCode1
Convolutional Sequence to Sequence LearningCode1
AIO-P: Expanding Neural Performance Predictors Beyond Image ClassificationCode1
Adversarial Example Detection for DNN Models: A Review and Experimental ComparisonCode1
CorGAN: Correlation-Capturing Convolutional Generative Adversarial Networks for Generating Synthetic Healthcare RecordsCode1
CosPGD: an efficient white-box adversarial attack for pixel-wise prediction tasksCode1
Counterfactual Generative NetworksCode1
Adversarial Examples in Deep Learning for Multivariate Time Series RegressionCode1
A Comprehensive Survey on Graph Neural NetworksCode1
COVID-CXNet: Detecting COVID-19 in Frontal Chest X-ray Images using Deep LearningCode1
CoWs on Pasture: Baselines and Benchmarks for Language-Driven Zero-Shot Object NavigationCode1
Cross-Domain Ensemble Distillation for Domain GeneralizationCode1
CrossFormer: A Versatile Vision Transformer Hinging on Cross-scale AttentionCode1
CMW-Net: Learning a Class-Aware Sample Weighting Mapping for Robust Deep LearningCode1
Class-Balanced Active Learning for Image ClassificationCode1
Cross-modulated Few-shot Image Generation for Colorectal Tissue ClassificationCode1
Benchmarking Pathology Feature Extractors for Whole Slide Image ClassificationCode1
Adversarially-Trained Deep Nets Transfer Better: Illustration on Image ClassificationCode1
Class-Balanced Distillation for Long-Tailed Visual RecognitionCode1
Curriculum By SmoothingCode1
Curriculum Temperature for Knowledge DistillationCode1
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable FeaturesCode1
Class-Aware Contrastive Semi-Supervised LearningCode1
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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