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 29262950 of 10420 papers

TitleStatusHype
Instance Temperature Knowledge DistillationCode0
Deployment of Image Analysis Algorithms under Prevalence ShiftsCode0
Beyond Accuracy: Metrics that Uncover What Makes a 'Good' Visual DescriptorCode0
Improving k-Means Clustering Performance with Disentangled Internal RepresentationsCode0
SynerMix: Synergistic Mixup Solution for Enhanced Intra-Class Cohesion and Inter-Class Separability in Image ClassificationCode0
An Architecture Combining Convolutional Neural Network (CNN) and Support Vector Machine (SVM) for Image ClassificationCode0
Improving Intervention Efficacy via Concept Realignment in Concept Bottleneck ModelsCode0
Improving Long-tailed Object Detection with Image-Level Supervision by Multi-Task Collaborative LearningCode0
Improving Memory Efficiency for Training KANs via Meta LearningCode0
DENSER: Deep Evolutionary Network Structured RepresentationCode0
Dense open-set recognition with synthetic outliers generated by Real NVPCode0
DenseNet Models for Tiny ImageNet ClassificationCode0
Between-class Learning for Image ClassificationCode0
Exploring Adversarial Robustness of Vision Transformers in the Spectral PerspectiveCode0
DenseNet for Breast Tumor Classification in Mammographic ImagesCode0
DenseNet approach to segmentation and classification of dermatoscopic skin lesions imagesCode0
Better Teacher Better Student: Dynamic Prior Knowledge for Knowledge DistillationCode0
Better Self-training for Image Classification through Self-supervisionCode0
Densely Connected Search Space for More Flexible Neural Architecture SearchCode0
Adaptive Stochastic Natural Gradient Method for One-Shot Neural Architecture SearchCode0
Improving Generalization of Batch Whitening by Convolutional Unit OptimizationCode0
Improving model calibration with accuracy versus uncertainty optimizationCode0
DGCNet: An Efficient 3D-Densenet based on Dynamic Group Convolution for Hyperspectral Remote Sensing Image ClassificationCode0
Improving Fairness in Image Classification via SketchingCode0
Dense and Diverse Capsule Networks: Making the Capsules Learn BetterCode0
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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