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 1701–1750 of 10419 papers

TitleStatusHype
Efficient-CapsNet: Capsule Network with Self-Attention RoutingCode1
Generative Multi-Label Zero-Shot LearningCode1
Meta Adversarial Training against Universal PatchesCode1
Advantages and Bottlenecks of Quantum Machine Learning for Remote SensingCode1
Malware Detection Using Frequency Domain-Based Image Visualization and Deep LearningCode1
Online Continual Learning in Image Classification: An Empirical SurveyCode1
DAF:re: A Challenging, Crowd-Sourced, Large-Scale, Long-Tailed Dataset For Anime Character RecognitionCode1
Analysis and evaluation of Deep Learning based Super-Resolution algorithms to improve performance in Low-Resolution Face RecognitionCode1
HarDNet-MSEG: A Simple Encoder-Decoder Polyp Segmentation Neural Network that Achieves over 0.9 Mean Dice and 86 FPSCode1
Hyperspectral Image Classification-Traditional to Deep Models: A Survey for Future ProspectsCode1
Counterfactual Generative NetworksCode1
Attention-Based Second-Order Pooling Network for Hyperspectral Image ClassificationCode1
Re-labeling ImageNet: from Single to Multi-Labels, from Global to Localized LabelsCode1
Big Self-Supervised Models Advance Medical Image ClassificationCode1
Robustness of on-device Models: Adversarial Attack to Deep Learning Models on Android AppsCode1
Mixup Without HesitationCode1
Quantum Tensor Network in Machine Learning: An Application to Tiny Object ClassificationCode1
Few-shot Image Classification: Just Use a Library of Pre-trained Feature Extractors and a Simple ClassifierCode1
Improve Object Detection with Feature-based Knowledge Distillation: Towards Accurate and Efficient DetectorsCode1
Recall Loss for Imbalanced Image Classification and Semantic SegmentationCode1
Iranis: A Large-scale Dataset of Farsi License Plate CharactersCode1
Co2L: Contrastive Continual LearningCode1
Kaleidoscope: An Efficient, Learnable Representation For All Structured Linear MapsCode1
Attention-Based Adaptive Spectral-Spatial Kernel ResNet for Hyperspectral Image ClassificationCode1
Deep Semantic Dictionary Learning for Multi-label Image ClassificationCode1
Training data-efficient image transformers & distillation through attentionCode1
A Second-Order Approach to Learning with Instance-Dependent Label NoiseCode1
Differentially Private Synthetic Medical Data Generation using Convolutional GANsCode1
FracBNN: Accurate and FPGA-Efficient Binary Neural Networks with Fractional ActivationsCode1
Generative Interventions for Causal LearningCode1
GANterfactual - Counterfactual Explanations for Medical Non-Experts using Generative Adversarial LearningCode1
FcaNet: Frequency Channel Attention NetworksCode1
When Machine Learning Meets Quantum Computers: A Case StudyCode1
Image and Text fusion for UPMC Food-101 \ BERT and CNNsCode1
DecAug: Out-of-Distribution Generalization via Decomposed Feature Representation and Semantic AugmentationCode1
Point TransformerCode1
Scaling Semantic Segmentation Beyond 1K Classes on a Single GPUCode1
WILDS: A Benchmark of in-the-Wild Distribution ShiftsCode1
Extended Few-Shot Learning: Exploiting Existing Resources for Novel TasksCode1
EfficientPose: Efficient Human Pose Estimation with Neural Architecture SearchCode1
Attentional-Biased Stochastic Gradient DescentCode1
Multi-direction Networks with Attentional Spectral Prior for Hyperspectral Image ClassificationCode1
Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label NoiseCode1
Multi-Objective Interpolation Training for Robustness to Label NoiseCode1
Towards Uncovering the Intrinsic Data Structures for Unsupervised Domain Adaptation using Structurally Regularized Deep ClusteringCode1
Large-scale Robust Deep AUC Maximization: A New Surrogate Loss and Empirical Studies on Medical Image ClassificationCode1
FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene UnderstandingCode1
Learning Equivariant RepresentationsCode1
Encoding the latent posterior of Bayesian Neural Networks for uncertainty quantificationCode1
Practical No-box Adversarial Attacks against DNNsCode1
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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