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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 5851–5900 of 10420 papers

TitleStatusHype
Is it all a cluster game? -- Exploring Out-of-Distribution Detection based on Clustering in the Embedding Space—0
Meta-Learning of NAS for Few-shot Learning in Medical Image Applications—0
2-speed network ensemble for efficient classification of incremental land-use/land-cover satellite image chips—0
Towards understanding deep learning with the natural clustering prior—0
One Network Doesn't Rule Them All: Moving Beyond Handcrafted Architectures in Self-Supervised Learning—0
InsCon:Instance Consistency Feature Representation via Self-Supervised Learning—0
Generalized but not Robust? Comparing the Effects of Data Modification Methods on Out-of-Domain Generalization and Adversarial Robustness—0
Meta Ordinal Regression Forest for Medical Image Classification with Ordinal Labels—0
On the Calibration of Pre-trained Language Models using Mixup Guided by Area Under the Margin and Saliency—0
UniVIP: A Unified Framework for Self-Supervised Visual Pre-training—0
Cross-View-Prediction: Exploring Contrastive Feature for Hyperspectral Image Classification—0
Scaling the Wild: Decentralizing Hogwild!-style Shared-memory SGDCode0
GSDA: Generative Adversarial Network-based Semi-Supervised Data Augmentation for Ultrasound Image Classification—0
Learning from Attacks: Attacking Variational Autoencoder for Improving Image Classification—0
Spatial Consistency Loss for Training Multi-Label Classifiers from Single-Label Annotations—0
Sparse Subspace Clustering for Concept Discovery (SSCCD)—0
Renyi Fair Information Bottleneck for Image Classification—0
Uni4Eye: Unified 2D and 3D Self-supervised Pre-training via Masked Image Modeling Transformer for Ophthalmic Image Classification—0
Multiscale Convolutional Transformer with Center Mask Pretraining for Hyperspectral Image Classification—0
Active Self-Semi-Supervised Learning for Few Labeled Samples—0
Dynamic Group Transformer: A General Vision Transformer Backbone with Dynamic Group Attention—0
Discriminability-Transferability Trade-Off: An Information-Theoretic PerspectiveCode0
Art-Attack: Black-Box Adversarial Attack via Evolutionary Art—0
Explaining Classifiers by Constructing Familiar ConceptsCode0
Dynamic ConvNets on Tiny Devices via Nested Sparsity—0
Graph Neural Networks for Image Classification and Reinforcement Learning using Graph representations—0
Fidelity of Interpretability Methods and Perturbation Artifacts in Neural Networks—0
FairPrune: Achieving Fairness Through Pruning for Dermatological Disease Diagnosis—0
Dynamic Backdoors with Global Average Pooling—0
Ensembles of Vision Transformers as a New Paradigm for Automated Classification in EcologyCode0
AdaFamily: A family of Adam-like adaptive gradient methods—0
Semi-supervised Learning using Robust LossCode0
ADVISE: ADaptive Feature Relevance and VISual Explanations for Convolutional Neural NetworksCode0
Visual Feature Encoding for GNNs on Road Networks—0
MIAShield: Defending Membership Inference Attacks via Preemptive Exclusion of Members—0
Aggregated Pyramid Vision Transformer: Split-transform-merge Strategy for Image Recognition without Convolutions—0
Continuous-Time Meta-Learning with Forward Mode Differentiation—0
Semi-supervised Deep Learning for Image Classification with Distribution Mismatch: A Survey—0
ESW Edge-Weights : Ensemble Stochastic Watershed Edge-Weights for Hyperspectral Image Classification—0
Amortized Proximal Optimization—0
Synergistic Network Learning and Label Correction for Noise-robust Image Classification—0
Neuro-Inspired Deep Neural Networks with Sparse, Strong ActivationsCode0
Accelerating Neural Architecture Exploration Across Modalities Using Genetic Algorithms—0
Goal-Oriented Communication for Edge Learning based on the Information Bottleneck—0
RRL:Regional Rotation Layer in Convolutional Neural Networks—0
Monogenic Wavelet Scattering Network for Texture Image Classification—0
Self-Training: A Survey—0
New Benchmark for Household Garbage Image Recognition—0
SUTD-PRCM Dataset and Neural Architecture Search Approach for Complex Metasurface Design—0
AutoCl : A Visual Interactive System for Automatic Deep Learning Classifier Recommendation Based on Models Performance—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