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

Showing 72267250 of 10420 papers

TitleStatusHype
Context-aware deep model compression for edge cloud computing0
Class-agnostic Object Detection0
Unsupervised part representation by Flow Capsules0
Improving Layer-wise Adaptive Rate Methods using Trust Ratio Clipping0
torchdistill: A Modular, Configuration-Driven Framework for Knowledge Distillation0
A Review of Open-World Learning and Steps Toward Open-World Learning Without LabelsCode0
StackMix: A complementary Mix algorithm0
Grafit: Learning fine-grained image representations with coarse labels0
Contrastive Representation Learning for Whole Brain Cytoarchitectonic Mapping in Histological Human Brain Sections0
Applying Convolutional Neural Networks to Data on Unstructured Meshes with Space-Filling CurvesCode0
Benchmarking Inference Performance of Deep Learning Models on Analog Devices0
Adam^+: A Stochastic Method with Adaptive Variance Reduction0
A New Periocular Dataset Collected by Mobile Devices in Unconstrained Scenarios0
Towards Imperceptible Universal Attacks on Texture Recognition0
Exploring Alternatives to Softmax FunctionCode0
Cancer image classification based on DenseNet model0
Unsupervised Difficulty Estimation with Action Scores0
Better Aggregation in Test-Time Augmentation0
Uncovering the Bias in Facial Expressions0
Learning Class Unique Features in Fine-Grained Visual Classification0
Dense open-set recognition with synthetic outliers generated by Real NVPCode0
An Effective Anti-Aliasing Approach for Residual Networks0
Large Scale Neural Architecture Search with Polyharmonic Splines0
DeepRepair: Style-Guided Repairing for DNNs in the Real-world Operational Environment0
On Focal Loss for Class-Posterior Probability Estimation: A Theoretical Perspective0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94Unverified
4DaViT-GTop 1 Accuracy90.4Unverified
5DaViT-HTop 1 Accuracy90.2Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90Unverified