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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3851–3900 of 10420 papers

TitleStatusHype
MOAT: Alternating Mobile Convolution and Attention Brings Strong Vision ModelsCode1
CLINICAL: Targeted Active Learning for Imbalanced Medical Image Classification—0
Distance Based Image Classification: A solution to generative classification's conundrum?Code0
Time-Varying Propensity Score to Bridge the Gap between the Past and Present—0
Learning with Limited Samples -- Meta-Learning and Applications to Communication Systems—0
Membership Inference Attacks Against Text-to-image Generation Models—0
Expediting Large-Scale Vision Transformer for Dense Prediction without Fine-tuningCode1
LPT: Long-tailed Prompt Tuning for Image ClassificationCode1
Towards a Unified View on Visual Parameter-Efficient Transfer LearningCode1
Feature Embedding by Template Matching as a ResNet Block—0
OCD: Learning to Overfit with Conditional Diffusion ModelsCode1
Systematic Generalization and Emergent Structures in Transformers Trained on Structured Tasks—0
A Smart Recycling Bin Using Waste Image Classification At The Edge—0
Multi Label Image Classification using Adaptive Graph Convolutional Networks (ML-AGCN)—0
Two-Stream Transformer for Multi-Label Image ClassificationCode1
Efficient Multilingual Multi-modal Pre-training through Triple Contrastive Loss—0
Visual Prompt Tuning for Few-Shot Text Classification—0
Offline Handwritten Amharic Character Recognition Using Few-shot LearningCode0
Learning Hierarchical Image Segmentation For Recognition and By RecognitionCode1
BayesFT: Bayesian Optimization for Fault Tolerant Neural Network ArchitectureCode0
An In-depth Study of Stochastic BackpropagationCode1
Momentum Tracking: Momentum Acceleration for Decentralized Deep Learning on Heterogeneous Data—0
A Novel Explainable Out-of-Distribution Detection Approach for Spiking Neural NetworksCode0
Identify ambiguous tasks combining crowdsourced labels by weighting Areas Under the Margin—0
Towards a Unified View of Affinity-Based Knowledge Distillation—0
Semi-Supervised Single-View 3D Reconstruction via Prototype Shape PriorsCode1
MobileViTv3: Mobile-Friendly Vision Transformer with Simple and Effective Fusion of Local, Global and Input FeaturesCode2
Spikformer: When Spiking Neural Network Meets TransformerCode2
Automatic Data Augmentation via Invariance-Constrained LearningCode0
Tuning of Mixture-of-Experts Mixed-Precision Neural Networks—0
Dilated Neighborhood Attention TransformerCode2
Increasing Model Generalizability for Unsupervised Domain Adaptation—0
Access Control with Encrypted Feature Maps for Object Detection Models—0
CompNet: A Designated Model to Handle Combinations of Images and Designed features—0
Deeply Supervised Layer Selective Attention Network: Towards Label-Efficient Learning for Medical Image Classification—0
Data Augmentation using Feature Generation for Volumetric Medical Images—0
Attention Spiking Neural Networks—0
CEC-CNN: A Consecutive Expansion-Contraction Convolutional Network for Very Small Resolution Medical Image Classification—0
Genetic Programming-Based Evolutionary Deep Learning for Data-Efficient Image Classification—0
EEG-based Image Feature Extraction for Visual Classification using Deep Learning—0
Stacking Ensemble Learning in Deep Domain Adaptation for Ophthalmic Image Classification—0
A GPU-accelerated Algorithm for Distinct Discriminant Canonical Correlation Network—0
Greybox XAI: a Neural-Symbolic learning framework to produce interpretable predictions for image classificationCode0
Optical Neural Ordinary Differential Equations—0
Improving Multi-fidelity Optimization with a Recurring Learning Rate for Hyperparameter Tuning—0
TAD: A Large-Scale Benchmark for Traffic Accidents Detection from Video SurveillanceCode1
Generalized Parametric Contrastive LearningCode2
Impact of Feedback Type on Explanatory Interactive Learning—0
Raising the Bar on the Evaluation of Out-of-Distribution Detection—0
Tiered Pruning for Efficient Differentialble Inference-Aware Neural Architecture Search—0
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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