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 5001–5050 of 10420 papers

TitleStatusHype
RA-CLIP: Retrieval Augmented Contrastive Language-Image Pre-Training—0
Neural Rate Estimator and Unsupervised Learning for Efficient Distributed Image Analytics in Split-DNN ModelsCode0
DropKey for Vision Transformer—0
Initialization Noise in Image Gradients and Saliency Maps—0
Building Vision Transformers with Hierarchy Aware Feature Aggregation—0
A New Dataset Based on Images Taken by Blind People for Testing the Robustness of Image Classification Models Trained for ImageNet CategoriesCode0
ProD: Prompting-To-Disentangle Domain Knowledge for Cross-Domain Few-Shot Image Classification—0
Boundary Unlearning: Rapid Forgetting of Deep Networks via Shifting the Decision Boundary—0
Boosting Whole Slide Image Classification from the Perspectives of Distribution, Correlation and Magnification—0
DIME-FM : DIstilling Multimodal and Efficient Foundation Models—0
Bias-Eliminating Augmentation Learning for Debiased Federated Learning—0
Scene-Aware Label Graph Learning for Multi-Label Image Classification—0
Rethinking Fast Fourier Convolution in Image Inpainting—0
Memory-Friendly Scalable Super-Resolution via Rewinding Lottery Ticket Hypothesis—0
PEFAT: Boosting Semi-Supervised Medical Image Classification via Pseudo-Loss Estimation and Feature Adversarial TrainingCode0
Adaptive Image Anonymization in the Context of Image Classification with Neural Networks—0
Personalized Semantics Excitation for Federated Image Classification—0
Automated Knowledge Distillation via Monte Carlo Tree SearchCode0
Image as a Foreign Language: BEiT Pretraining for Vision and Vision-Language Tasks—0
iCLIP: Bridging Image Classification and Contrastive Language-Image Pre-Training for Visual RecognitionCode0
Growing a Brain with Sparsity-Inducing Generation for Continual LearningCode0
Temporal-Coded Spiking Neural Networks with Dynamic Firing Threshold: Learning with Event-Driven Backpropagation—0
Accelerate adversarial training with loss guided propagation for robust image classificationCode0
Co-Training 2L Submodels for Visual Recognition—0
GoogLe2Net: Going Transverse with Convolutions—0
Tiny Updater: Towards Efficient Neural Network-Driven Software UpdatingCode0
Quantum-Inspired Spectral-Spatial Pyramid Network for Hyperspectral Image Classification—0
Chest X-Ray Images Classification with CNNCode0
DiRaC-I: Identifying Diverse and Rare Training Classes for Zero-Shot Learning—0
TransIFC: Invariant Cues-aware Feature Concentration Learning for Efficient Fine-grained Bird Image Classification—0
Machine Learning and Thermography Applied to the Detection and Classification of Cracks in Building—0
On Learning the Structure of Clusters in Graphs—0
Thermal Heating in ReRAM Crossbar Arrays: Challenges and Solutions—0
Sparse Mixture Once-for-all Adversarial Training for Efficient In-Situ Trade-Off Between Accuracy and Robustness of DNNs—0
Langevin algorithms for very deep Neural Networks with application to image classificationCode0
Attribute-Guided Multi-Level Attention Network for Fine-Grained Fashion RetrievalCode0
Saliency-Augmented Memory Completion for Continual LearningCode0
Hyperspherical Loss-Aware Ternary Quantization—0
LMFLOSS: A Hybrid Loss For Imbalanced Medical Image ClassificationCode0
When are Lemons Purple? The Concept Association Bias of Vision-Language Models—0
Understanding and Improving the Role of Projection Head in Self-Supervised Learning—0
Class Prototype-based Cleaner for Label Noise LearningCode0
Decision-making and control with diffractive optical networksCode0
Calibrating Deep Neural Networks using Explicit Regularisation and Dynamic Data Pruning—0
Temporal Output Discrepancy for Loss Estimation-based Active Learning—0
DDIPNet and DDIPNet+: Discriminant Deep Image Prior Networks for Remote Sensing Image Classification—0
Galaxy Image Classification using Hierarchical Data Learning with Weighted Sampling and Label SmoothingCode0
Unified Framework for Histopathology Image Augmentation and Classification via Generative Models—0
Improving Pre-Trained Weights Through Meta-Heuristics Fine-TuningCode0
Rethinking Label Smoothing on Multi-hop Question AnsweringCode0
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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