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 1201–1250 of 10419 papers

TitleStatusHype
Augmented Neural ODEsCode1
Augmenting Convolutional networks with attention-based aggregationCode1
Explanation as a Watermark: Towards Harmless and Multi-bit Model Ownership Verification via Watermarking Feature AttributionCode1
Exploiting Label Skews in Federated Learning with Model ConcatenationCode1
NoisyNN: Exploring the Impact of Information Entropy Change in Learning SystemsCode1
Exploring Vision Transformers for Fine-grained ClassificationCode1
A Survey on Transferability of Adversarial Examples across Deep Neural NetworksCode1
Nested Hierarchical Transformer: Towards Accurate, Data-Efficient and Interpretable Visual UnderstandingCode1
CellGAN: Conditional Cervical Cell Synthesis for Augmenting Cytopathological Image ClassificationCode1
CEFHRI: A Communication Efficient Federated Learning Framework for Recognizing Industrial Human-Robot InteractionCode1
BiasPruner: Debiased Continual Learning for Medical Image ClassificationCode1
AugMix: A Simple Data Processing Method to Improve Robustness and UncertaintyCode1
AugNet: End-to-End Unsupervised Visual Representation Learning with Image AugmentationCode1
Failure Detection in Medical Image Classification: A Reality Check and Benchmarking TestbedCode1
Algorithm-hardware Co-design for Deformable ConvolutionCode1
PAD-Net: An Efficient Framework for Dynamic NetworksCode1
A Unified Algebraic Perspective on Lipschitz Neural NetworksCode1
CLIP-guided Federated Learning on Heterogeneous and Long-Tailed DataCode1
Adapting Grad-CAM for Embedding NetworksCode1
Fast Convex Optimization for Two-Layer ReLU Networks: Equivalent Model Classes and Cone DecompositionsCode1
Bias Loss for Mobile Neural NetworksCode1
Faster Meta Update Strategy for Noise-Robust Deep LearningCode1
Bidirectional-Convolutional LSTM Based Spectral-Spatial Feature Learning for Hyperspectral Image ClassificationCode1
CheXFusion: Effective Fusion of Multi-View Features using Transformers for Long-Tailed Chest X-Ray ClassificationCode1
CHEX: CHannel EXploration for CNN Model CompressionCode1
Fast Hierarchical Games for Image ExplanationsCode1
Early-Learning Regularization Prevents Memorization of Noisy LabelsCode1
Fast-SNN: Fast Spiking Neural Network by Converting Quantized ANNCode1
BinaryViT: Pushing Binary Vision Transformers Towards Convolutional ModelsCode1
A Universal Representation Transformer Layer for Few-Shot Image ClassificationCode1
A Bregman Learning Framework for Sparse Neural NetworksCode1
DynamicViT: Efficient Vision Transformers with Dynamic Token SparsificationCode1
Revisiting the Importance of Amplifying Bias for DebiasingCode1
FCCNs: Fully Complex-valued Convolutional Networks using Complex-valued Color Model and Loss FunctionCode1
Circumventing Outliers of AutoAugment with Knowledge DistillationCode1
AutoDC: Automated data-centric processingCode1
Feature Extraction for Hyperspectral Imagery: The Evolution from Shallow to Deep (Overview and Toolbox)Code1
AutoDiCE: Fully Automated Distributed CNN Inference at the EdgeCode1
Class-Aware Contrastive Semi-Supervised LearningCode1
Class-Balanced Loss Based on Effective Number of SamplesCode1
Class Adaptive Network CalibrationCode1
Aggregated Residual Transformations for Deep Neural NetworksCode1
Class-Aware Patch Embedding Adaptation for Few-Shot Image ClassificationCode1
Class-Balanced Distillation for Long-Tailed Visual RecognitionCode1
Auto Learning AttentionCode1
AutoLRS: Automatic Learning-Rate Schedule by Bayesian Optimization on the FlyCode1
Bi-directional Feature Reconstruction Network for Fine-Grained Few-Shot Image ClassificationCode1
FedMLP: Federated Multi-Label Medical Image Classification under Task HeterogeneityCode1
Automated detection of COVID-19 cases from chest X-ray images using deep neural network and XGBoostCode1
DynaMixer: A Vision MLP Architecture with Dynamic MixingCode1
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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