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 85018525 of 10420 papers

TitleStatusHype
A Rate-Distortion Framework for Explaining Neural Network DecisionsCode0
Defining Quantum Neural Networks via Quantum Time Evolution0
Derivative Manipulation for General Example WeightingCode1
Shredder: Learning Noise Distributions to Protect Inference PrivacyCode1
ProbAct: A Probabilistic Activation Function for Deep Neural NetworksCode1
Let's Agree to Agree: Neural Networks Share Classification Order on Real Datasets0
Robust Classification using Robust Feature Augmentation0
Why do These Match? Explaining the Behavior of Image Similarity ModelsCode0
SuperCaptioning: Image Captioning Using Two-dimensional Word Embedding0
DIANet: Dense-and-Implicit Attention NetworkCode1
Bivariate Beta-LSTMCode0
Cold Case: The Lost MNIST DigitsCode0
Adversarial Distillation for Ordered Top-k Attacks0
Additive Noise Annealing and Approximation Properties of Quantized Neural NetworksCode0
Fully Hyperbolic Convolutional Neural Networks0
Semi-supervised GAN for Classification of Multispectral Imagery Acquired by UAVs0
FasTrCaps: An Integrated Framework for Fast yet Accurate Training of Capsule NetworksCode0
On the Learning Dynamics of Two-layer Nonlinear Convolutional Neural Networks0
Multi-Sample Dropout for Accelerated Training and Better GeneralizationCode0
A Direct Approach to Robust Deep Learning Using Adversarial NetworksCode0
The Convolutional Tsetlin MachineCode0
Tucker Decomposition Network: Expressive Power and Comparison0
Spatial Group-wise Enhance: Improving Semantic Feature Learning in Convolutional NetworksCode0
Segmentation-Aware Hyperspectral Image Classification0
Fine-grained Optimization of Deep Neural NetworksCode0
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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
10RevCol-HTop 1 Accuracy90Unverified