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 3151–3200 of 10419 papers

TitleStatusHype
Class-Conditioned Transformation for Enhanced Robust Image ClassificationCode0
GeoNet: Benchmarking Unsupervised Adaptation across Geographies—0
Text-to-Image Diffusion Models are Zero-Shot ClassifiersCode0
EVA-CLIP: Improved Training Techniques for CLIP at ScaleCode1
Galaxy Classification Using Transfer Learning and Ensemble of CNNs With Multiple Colour Spaces—0
Boosting Few-Shot Text Classification via Distribution Estimation—0
Deep transfer learning for detecting Covid-19, Pneumonia and Tuberculosis using CXR images -- A Review—0
Freestyle Layout-to-Image SynthesisCode1
Image Moment Invariants to Rotational Motion Blur—0
Active Finetuning: Exploiting Annotation Budget in the Pretraining-Finetuning ParadigmCode1
FastViT: A Fast Hybrid Vision Transformer using Structural ReparameterizationCode3
Optimal Smoothing Distribution Exploration for Backdoor Neutralization in Deep Learning-based Traffic Systems—0
CIFAKE: Image Classification and Explainable Identification of AI-Generated Synthetic Images—0
Category Query Learning for Human-Object Interaction ClassificationCode1
PIAT: Parameter Interpolation based Adversarial Training for Image Classification—0
Prompt Tuning based Adapter for Vision-Language Model AdaptionCode1
Take 5: Interpretable Image Classification with a Handful of FeaturesCode1
The effectiveness of MAE pre-pretraining for billion-scale pretrainingCode1
First Session Adaptation: A Strong Replay-Free Baseline for Class-Incremental Learning—0
Exploring Visual Prompts for Whole Slide Image Classification with Multiple Instance Learning—0
MMFormer: Multimodal Transformer Using Multiscale Self-Attention for Remote Sensing Image Classification—0
A Simple and Generic Framework for Feature Distillation via Channel-wise Transformation—0
Unsupervised Domain Adaptation for Training Event-Based Networks Using Contrastive Learning and Uncorrelated Conditioning—0
SCALES: Boost Binary Neural Network for Image Super-Resolution with Efficient Scalings—0
LD-ZNet: A Latent Diffusion Approach for Text-Based Image Segmentation—0
Deployment of Image Analysis Algorithms under Prevalence ShiftsCode0
Exploring the Benefits of Visual Prompting in Differential PrivacyCode0
Machine Learning for Brain Disorders: Transformers and Visual Transformers—0
Boundary Unlearning—0
ViC-MAE: Self-Supervised Representation Learning from Images and Video with Contrastive Masked AutoencodersCode0
Creating Ensembles of Classifiers through UMDA for Aerial Scene Classification—0
Bias mitigation techniques in image classification: fair machine learning in human heritage collections—0
Understanding the Role of the Projector in Knowledge DistillationCode1
TWINS: A Fine-Tuning Framework for Improved Transferability of Adversarial Robustness and GeneralizationCode1
Parameter-Free Channel Attention for Image Classification and Super-Resolution—0
DiffMIC: Dual-Guidance Diffusion Network for Medical Image ClassificationCode1
Supervision Interpolation via LossMix: Generalizing Mixup for Object Detection and Beyond—0
Uncertainty-informed Mutual Learning for Joint Medical Image Classification and SegmentationCode1
The Cascaded Forward Algorithm for Neural Network TrainingCode1
Extracting the Brain-like Representation by an Improved Self-Organizing Map for Image ClassificationCode0
A New Benchmark: On the Utility of Synthetic Data with Blender for Bare Supervised Learning and Downstream Domain AdaptationCode1
Rethinking Model Ensemble in Transfer-based Adversarial AttacksCode1
Unsupervised domain adaptation by learning using privileged information—0
Conditional Synthetic Food Image Generation—0
Agnostic Multi-Robust Learning Using ERM—0
Practicality of generalization guarantees for unsupervised domain adaptation with neural networks—0
Task-specific Fine-tuning via Variational Information Bottleneck for Weakly-supervised Pathology Whole Slide Image ClassificationCode1
Visual Prompt Based Personalized Federated Learning—0
BiFormer: Vision Transformer with Bi-Level Routing AttentionCode2
DeepMIM: Deep Supervision for Masked Image ModelingCode1
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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
5DaViT-HTop 1 Accuracy90.2—Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 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
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified