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 1576–1600 of 10420 papers

TitleStatusHype
3D-Convolution Guided Spectral-Spatial Transformer for Hyperspectral Image ClassificationCode0
Nested-TNT: Hierarchical Vision Transformers with Multi-Scale Feature Processing—0
On-board classification of underwater images using hybrid classical-quantum CNN based method—0
Next Generation Loss Function for Image ClassificationCode1
A Hybrid Generative and Discriminative PointNet on Unordered Point Sets—0
Transformer-Based Classification Outcome Prediction for Multimodal Stroke Treatment—0
A Perspective on Deep Vision Performance with Standard Image and Video Codecs—0
Concept Induction using LLMs: a user experiment for assessment—0
An Experimental Study on Exploring Strong Lightweight Vision Transformers via Masked Image Modeling Pre-TrainingCode2
A Progressive Framework of Vision-language Knowledge Distillation and Alignment for Multilingual Scene—0
GhostNetV3: Exploring the Training Strategies for Compact Models—0
InfoMatch: Entropy Neural Estimation for Semi-Supervised Image ClassificationCode1
Achieving Rotation Invariance in Convolution Operations: Shifting from Data-Driven to Mechanism-Assured—0
Supervised Contrastive Vision Transformer for Breast Histopathological Image Classification—0
MobileNetV4 -- Universal Models for the Mobile EcosystemCode3
Med-MoE: Mixture of Domain-Specific Experts for Lightweight Medical Vision-Language ModelsCode2
Lighter, Better, Faster Multi-Source Domain Adaptation with Gaussian Mixture Models and Optimal TransportCode0
Tree Bandits for Generative Bayes—0
Assessing The Impact of CNN Auto Encoder-Based Image Denoising on Image Classification TasksCode0
Vocabulary-free Image Classification and Semantic SegmentationCode0
A variable metric proximal stochastic gradient method: an application to classification problemsCode0
Distributed Federated Learning-Based Deep Learning Model for Privacy MRI Brain Tumor Detection—0
Pseudo-label Learning with Calibrated Confidence Using an Energy-based Model—0
Interaction as Explanation: A User Interaction-based Method for Explaining Image Classification Models—0
Coreset Selection for Object Detection—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