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 13011325 of 10419 papers

TitleStatusHype
Averaging Weights Leads to Wider Optima and Better GeneralizationCode1
ExCon: Explanation-driven Supervised Contrastive Learning for Image ClassificationCode1
CPrune: Compiler-Informed Model Pruning for Efficient Target-Aware DNN ExecutionCode1
EXplainable Neural-Symbolic Learning (X-NeSyL) methodology to fuse deep learning representations with expert knowledge graphs: the MonuMAI cultural heritage use caseCode1
A Visual Analytics Framework for Explaining and Diagnosing Transfer Learning ProcessesCode1
Explaining in Style: Training a GAN to explain a classifier in StyleSpaceCode1
AMC-Loss: Angular Margin Contrastive Loss for Improved Explainability in Image ClassificationCode1
Discovering and Mitigating Visual Biases through Keyword ExplanationCode1
Adaptive DropBlock Enhanced Generative Adversarial Networks for Hyperspectral Image ClassificationCode1
AwesomeMeta+: A Mixed-Prototyping Meta-Learning System Supporting AI Application Design AnywhereCode1
A Whac-A-Mole Dilemma: Shortcuts Come in Multiples Where Mitigating One Amplifies OthersCode1
CorGAN: Correlation-Capturing Convolutional Generative Adversarial Networks for Generating Synthetic Healthcare RecordsCode1
CoProNN: Concept-based Prototypical Nearest Neighbors for Explaining Vision ModelsCode1
Extremely Lightweight Quantization Robust Real-Time Single-Image Super Resolution for Mobile DevicesCode1
CosPGD: an efficient white-box adversarial attack for pixel-wise prediction tasksCode1
Babel-ImageNet: Massively Multilingual Evaluation of Vision-and-Language RepresentationsCode1
Failure Detection in Medical Image Classification: A Reality Check and Benchmarking TestbedCode1
Fair Contrastive Learning for Facial Attribute ClassificationCode1
Fast and Accurate Gigapixel Pathological Image Classification with Hierarchical Distillation Multi-Instance LearningCode1
Backdoor Attacks on Crowd CountingCode1
Fast and Private Inference of Deep Neural Networks by Co-designing Activation FunctionsCode1
Fast AutoAugmentCode1
Faster Meta Update Strategy for Noise-Robust Deep LearningCode1
Convolutional Xformers for VisionCode1
No Routing Needed Between CapsulesCode1
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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