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 30513075 of 10420 papers

TitleStatusHype
Autoencoders with Intrinsic Dimension Constraints for Learning Low Dimensional Image Representations0
Teacher Network Calibration Improves Cross-Quality Knowledge DistillationCode0
Beta-Rank: A Robust Convolutional Filter Pruning Method For Imbalanced Medical Image AnalysisCode0
From Online Behaviours to Images: A Novel Approach to Social Bot Detection0
ODSmoothGrad: Generating Saliency Maps for Object Detectors0
Real-Time Helmet Violation Detection Using YOLOv5 and Ensemble Learning0
Phantom Embeddings: Using Embedding Space for Model Regularization in Deep Neural Networks0
DINOv2: Learning Robust Visual Features without SupervisionCode6
Scale Federated Learning for Label Set Mismatch in Medical Image ClassificationCode0
Interpretable Weighted Siamese Network to Predict the Time to Onset of Alzheimer's Disease from MRI ImagesCode0
Enhancing Self-Supervised Learning for Remote Sensing with Elevation Data: A Case Study with Scarce And High Level Semantic LabelsCode0
Dynamic Mobile-Former: Strengthening Dynamic Convolution with Attention and Residual Connection in Kernel SpaceCode0
Boosting Convolutional Neural Networks with Middle Spectrum Grouped ConvolutionCode1
TransHP: Image Classification with Hierarchical PromptingCode1
Remote Sensing Change Detection With Transformers Trained from ScratchCode1
ProtoDiv: Prototype-guided Division of Consistent Pseudo-bags for Whole-slide Image Classification0
Optimizing Multi-Domain Performance with Active Learning-based Improvement Strategies0
Learning Accurate Performance Predictors for Ultrafast Automated Model CompressionCode0
Towards Evaluating Explanations of Vision Transformers for Medical ImagingCode1
Semantic-Aware Mixup for Domain GeneralizationCode0
Unicom: Universal and Compact Representation Learning for Image RetrievalCode2
SpectralDiff: A Generative Framework for Hyperspectral Image Classification with Diffusion ModelsCode1
Continual Diffusion: Continual Customization of Text-to-Image Diffusion with C-LoRA0
SamurAI: A Versatile IoT Node With Event-Driven Wake-Up and Embedded ML Acceleration0
A priori compression of convolutional neural networks for wave simulators0
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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