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 8551–8600 of 10420 papers

TitleStatusHype
The iMaterialist Fashion Attribute DatasetCode0
Pay Attention to Convolution Filters: Towards Fast and Accurate Fine-Grained Transfer Learning—0
Indoor image representation by high-level semantic features—0
Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical BayesCode0
Continual and Multi-Task Architecture SearchCode0
Manifold Graph with Learned Prototypes for Semi-Supervised Image Classification—0
Band Attention Convolutional Networks For Hyperspectral Image Classification—0
Simultaneously Learning Architectures and Features of Deep Neural Networks—0
Weight Agnostic Neural NetworksCode0
Weakly-supervised Compositional FeatureAggregation for Few-shot Recognition—0
Zero-Shot Image Classification Using Coupled Dictionary Embedding—0
SymNet: Symmetrical Filters in Convolutional Neural Networks—0
A Closed-Form Learned Pooling for Deep Classification Networks—0
BDNet: Bengali Handwritten Numeral Digit Recognition based on Densely connected Convolutional Neural NetworksCode0
CNN depth analysis with different channel inputs for Acoustic Scene Classification—0
A Preliminary Study on Data Augmentation of Deep Learning for Image Classification—0
Pixel DAG-Recurrent Neural Network for Spectral-Spatial Hyperspectral Image Classification—0
Semi-supervised Complex-valued GAN for Polarimetric SAR Image Classification—0
Using learned optimizers to make models robust to input noise—0
Outlier Exposure with Confidence Control for Out-of-Distribution DetectionCode0
A New Compensatory Genetic Algorithm-Based Method for Effective Compressed Multi-function Convolutional Neural Network Model Selection with Multi-Objective Optimization—0
DiCENet: Dimension-wise Convolutions for Efficient NetworksCode0
Towards Non-I.I.D. Image Classification: A Dataset and Baselines—0
Learning Representations of Graph Data -- A Survey—0
Cell image classification: a comparative overviewCode0
Adversarial Explanations for Understanding Image Classification Decisions and Improved Neural Network RobustnessCode0
Variational Resampling Based Assessment of Deep Neural Networks under Distribution ShiftCode0
Unsupervised Feature Learning with K-means and An Ensemble of Deep Convolutional Neural Networks for Medical Image Classification—0
TensorNetwork for Machine LearningCode0
StyleNAS: An Empirical Study of Neural Architecture Search to Uncover Surprisingly Fast End-to-End Universal Style Transfer Networks—0
Should Adversarial Attacks Use Pixel p-Norm?—0
Bad Global Minima Exist and SGD Can Reach ThemCode0
Iterative Self-Learning: Semi-Supervised Improvement to Dataset Volumes and Model Accuracy—0
Playing the lottery with rewards and multiple languages: lottery tickets in RL and NLP—0
Robust Attacks against Multiple ClassifiersCode0
PI-Net: A Deep Learning Approach to Extract Topological Persistence ImagesCode0
Collage Inference: Achieving low tail latency during distributed image classification using coded redundancy models—0
c-Eval: A Unified Metric to Evaluate Feature-based Explanations via Perturbation—0
Multi-way Encoding for Robustness—0
Visual Confusion Label Tree For Image Classification—0
Visual Tree Convolutional Neural Network in Image Classification—0
Embedded hyper-parameter tuning by Simulated AnnealingCode0
Information Competing Process for Learning Diversified RepresentationsCode0
Constructing Energy-efficient Mixed-precision Neural Networks through Principal Component Analysis for Edge IntelligenceCode0
An Introduction to Deep Morphological Networks—0
Geo-Aware Networks for Fine-Grained RecognitionCode0
Deeply-supervised Knowledge SynergyCode0
Achieving Generalizable Robustness of Deep Neural Networks by Stability Training—0
Hierarchical Auxiliary Learning—0
Learning Representations by Maximizing Mutual Information Across ViewsCode0
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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