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 5401–5450 of 10420 papers

TitleStatusHype
Evaluation of Deep Neural Network Domain Adaptation Techniques for Image RecognitionCode1
Multi-Semantic Image Recognition Model and Evaluating Index for explaining the deep learning models—0
DeepPSL: End-to-end perception and reasoning—0
A Strong Baseline for the VIPriors Data-Efficient Image Classification Challenge—0
Accelerated PDEs for Construction and Theoretical Analysis of an SGD Extension—0
ST-MAML: A Stochastic-Task based Method for Task-Heterogeneous Meta-Learning—0
Audio-to-Image Cross-Modal Generation—0
Compressive Visual RepresentationsCode1
Federated Deep Learning with Bayesian Privacy—0
Cluster Attack: Query-based Adversarial Attacks on Graphs with Graph-Dependent PriorsCode0
Training on Test Data with Bayesian Adaptation for Covariate Shift—0
Predicting Driver Self-Reported Stress by Analyzing the Road Scene—0
Disentangled Feature Representation for Few-shot Image ClassificationCode1
Frequency Disentangled Residual Network—0
FedProc: Prototypical Contrastive Federated Learning on Non-IID dataCode1
Classification of COVID-19 from CXR Images in a 15-class Scenario: an Attempt to Avoid Bias in the System—0
Distribution-sensitive Information Retention for Accurate Binary Neural Network—0
BiTr-Unet: a CNN-Transformer Combined Network for MRI Brain Tumor SegmentationCode1
From images in the wild to video-informed image classification—0
Frequency Pooling: Shift-Equivalent and Anti-Aliasing Downsampling—0
A Multi-stage Transfer Learning Framework for Diabetic Retinopathy Grading on Small Data—0
FooBaR: Fault Fooling Backdoor Attack on Neural Network TrainingCode0
Partial sensitivity analysis in differential privacyCode0
Multi-Domain Few-Shot Learning and Dataset for Agricultural Applications—0
Balanced-MixUp for Highly Imbalanced Medical Image ClassificationCode1
GhostShiftAddNet: More Features from Energy-Efficient OperationsCode0
Explaining Convolutional Neural Networks by Tagging Filters—0
Audio-Visual Speech Recognition is Worth 32328 Voxels—0
Class incremental learning for video action classification—0
Ontology-based n-ball Concept Embeddings Informing Few-shot Image Classification—0
Splitfed learning without client-side synchronization: Analyzing client-side split network portion size to overall performance—0
UNetFormer: A UNet-like Transformer for Efficient Semantic Segmentation of Remote Sensing Urban Scene ImageryCode2
The Unreasonable Effectiveness of the Final Batch Normalization Layer—0
PP-LCNet: A Lightweight CPU Convolutional Neural NetworkCode1
Decision Tree Learning with Spatial Modal Logics—0
Transformer-Unet: Raw Image Processing with Unet—0
Topological Structure and Semantic Information Transfer Network for Cross-Scene Hyperspectral Image ClassificationCode1
Exploiting Activation based Gradient Output Sparsity to Accelerate Backpropagation in CNNs—0
Deep Algorithmic Question Answering: Towards a Compositionally Hybrid AI for Algorithmic Reasoning—0
Partner-Assisted Learning for Few-Shot Image Classification—0
Sign-MAML: Efficient Model-Agnostic Meta-Learning by SignSGDCode0
A trainable monogenic ConvNet layer robust in front of large contrast changes in image classificationCode0
AdaPruner: Adaptive Channel Pruning and Effective Weights Inheritance—0
Robust Contrastive Active Learning with Feature-guided Query Strategies—0
Task Guided Compositional Representation Learning for ZDA—0
PAT: Pseudo-Adversarial Training For Detecting Adversarial Videos—0
Fine-Grained Few Shot Learning with Foreground Object Transformation—0
Check Your Other Door! Creating Backdoor Attacks in the Frequency Domain—0
BioLCNet: Reward-modulated Locally Connected Spiking Neural NetworksCode0
Sparse MLP for Image Recognition: Is Self-Attention Really Necessary?Code1
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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