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 34513475 of 10420 papers

TitleStatusHype
Improving k-Means Clustering Performance with Disentangled Internal RepresentationsCode0
Improved Training Speed, Accuracy, and Data Utilization Through Loss Function OptimizationCode0
A Method of Moments Embedding Constraint and its Application to Semi-Supervised LearningCode0
Attacking by Aligning: Clean-Label Backdoor Attacks on Object DetectionCode0
Improved robustness of reinforcement learning policies upon conversion to spiking neuronal network platforms applied to ATARI gamesCode0
Deep Layer AggregationCode0
BR-NPA: A Non-Parametric High-Resolution Attention Model to improve the Interpretability of AttentionCode0
Improved efficient capsule network for Kuzushiji-MNIST benchmark dataset classificationCode0
Deep Intrinsic Decomposition with Adversarial Learning for Hyperspectral Image ClassificationCode0
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency MapsCode0
A Comprehensive guide to Bayesian Convolutional Neural Network with Variational InferenceCode0
Improved Gradient based Adversarial Attacks for Quantized NetworksCode0
S4L: Self-Supervised Semi-Supervised LearningCode0
Improved Activation Clipping for Universal Backdoor Mitigation and Test-Time DetectionCode0
Deep Hybrid Architecture for Very Low-Resolution Image Classification Using Capsule AttentionCode0
Adversarial Attack and Defense on Graph Data: A SurveyCode0
Improving Long-tailed Object Detection with Image-Level Supervision by Multi-Task Collaborative LearningCode0
Impact of Fully Connected Layers on Performance of Convolutional Neural Networks for Image ClassificationCode0
Impact of ImageNet Model Selection on Domain AdaptationCode0
DeepGraviLens: a Multi-Modal Architecture for Classifying Gravitational Lensing DataCode0
Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed TrainingCode0
Implicit Generative Prior for Bayesian Neural NetworksCode0
CHEF: A Cheap and Fast Pipeline for Iteratively Cleaning Label Uncertainties (Technical Report)Code0
Efficient Search for Customized Activation Functions with Gradient DescentCode0
Deep Gradient Compression Reduce the Communication Bandwidth For distributed TraningCode0
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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
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
6DaViT-HTop 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