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

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Showing 701–750 of 10419 papers

TitleStatusHype
CvT: Introducing Convolutions to Vision TransformersCode1
Analysis and evaluation of Deep Learning based Super-Resolution algorithms to improve performance in Low-Resolution Face RecognitionCode1
CLIP the Gap: A Single Domain Generalization Approach for Object DetectionCode1
A Novel lightweight Convolutional Neural Network, ExquisiteNetV2Code1
DarkneTZ: Towards Model Privacy at the Edge using Trusted Execution EnvironmentsCode1
DARTS: Differentiable Architecture SearchCode1
FocusNet: Classifying Better by Focusing on Confusing ClassesCode1
DATA: Domain-Aware and Task-Aware Self-supervised LearningCode1
Data-Efficient Deep Learning Method for Image Classification Using Data Augmentation, Focal Cosine Loss, and EnsembleCode1
Data Feedback Loops: Model-driven Amplification of Dataset BiasesCode1
Anytime Continual Learning for Open Vocabulary ClassificationCode1
CNN Filter DB: An Empirical Investigation of Trained Convolutional FiltersCode1
DC3DCD: unsupervised learning for multiclass 3D point cloud change detectionCode1
DCN-T: Dual Context Network with Transformer for Hyperspectral Image ClassificationCode1
Combining Metric Learning and Attention Heads For Accurate and Efficient Multilabel Image ClassificationCode1
Deblurring Masked Autoencoder is Better Recipe for Ultrasound Image RecognitionCode1
DiG-IN: Diffusion Guidance for Investigating Networks -- Uncovering Classifier Differences Neuron Visualisations and Visual Counterfactual ExplanationsCode1
Decision Stream: Cultivating Deep Decision TreesCode1
Continual Learning Using a Kernel-Based Method Over Foundation ModelsCode1
DAM: Dynamic Adapter Merging for Continual Video QA LearningCode1
Deep CNNs Meet Global Covariance Pooling: Better Representation and GeneralizationCode1
Deep Complex NetworksCode1
DeepEMD: Differentiable Earth Mover's Distance for Few-Shot LearningCode1
Analyzing Vision Transformers for Image Classification in Class Embedding SpaceCode1
Deep Fast Vision: Accelerated Deep Transfer Learning Vision Prototyping and BeyondCode1
Deep Fast Vision: A Python Library for Accelerated Deep Transfer Learning Vision PrototypingCode1
Deep-Learning-Based Aerial Image Classification for Emergency Response Applications Using Unmanned Aerial VehiclesCode1
Deep Learning Based Brain Tumor Segmentation: A SurveyCode1
AdaScale SGD: A User-Friendly Algorithm for Distributed TrainingCode1
An Analysis on Ensemble Learning optimized Medical Image Classification with Deep Convolutional Neural NetworksCode1
Deep Network Ensemble Learning applied to Image Classification using CNN TreesCode1
Deep Networks with Stochastic DepthCode1
A Data Set and a Convolutional Model for Iconography Classification in PaintingsCode1
DHP: Differentiable Meta Pruning via HyperNetworksCode1
Clean-Label Backdoor Attacks on Video Recognition ModelsCode1
CLCNet: Rethinking of Ensemble Modeling with Classification Confidence NetworkCode1
Deep Semantic-Visual Alignment for Zero-Shot Remote Sensing Image Scene ClassificationCode1
Deep Subdomain Adaptation Network for Image ClassificationCode1
AdaViT: Adaptive Tokens for Efficient Vision TransformerCode1
An Overview of Deep Learning Architectures in Few-Shot Learning DomainCode1
Deep Unlearning: Fast and Efficient Gradient-free Approach to Class ForgettingCode1
DeepViT: Towards Deeper Vision TransformerCode1
CleanNet: Transfer Learning for Scalable Image Classifier Training with Label NoiseCode1
DeiT-LT Distillation Strikes Back for Vision Transformer Training on Long-Tailed DatasetsCode1
Delving into Out-of-Distribution Detection with Medical Vision-Language ModelsCode1
Demonstrating the Efficacy of Kolmogorov-Arnold Networks in Vision TasksCode1
Dendritic Learning-incorporated Vision Transformer for Image RecognitionCode1
DenoiseRep: Denoising Model for Representation LearningCode1
Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODECode1
Almost-Orthogonal Layers for Efficient General-Purpose Lipschitz NetworksCode1
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All datasetsImageNetCIFAR-10CIFAR-100STL-10ObjectNetMNISTSVHNiNaturalist 2018ImageNet ReaLFlowers-102Clothing1Mmini WebVision 1.0

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91—Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98—Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94—Unverified
4DaViT-GTop 1 Accuracy90.4—Unverified
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2—Unverified
6DaViT-HTop 1 Accuracy90.2—Unverified
7SwinV2-GTop 1 Accuracy90.17—Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1—Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05—Unverified
10RevCol-HTop 1 Accuracy90—Unverified