SOTAVerified

Dataset Generation

The task involves enhancing the training of target application (e.g. autonomous driving systems) by generating datasets of diverse and critical elements (e.g. traffic scenarios). Traditional methods rely on expensive and limited datasets, which often fail to capture rare but essential situations that can pose risks during testing.

Papers

Showing 91100 of 308 papers

TitleStatusHype
IrrMap: A Large-Scale Comprehensive Dataset for Irrigation Method MappingCode0
Bag of Views: An Appearance-based Approach to Next-Best-View Planning for 3D ReconstructionCode0
Improving Sentence Embeddings with Automatic Generation of Training Data Using Few-shot ExamplesCode0
JABBERWOCK: A Tool for WebAssembly Dataset Generation and Its Application to Malicious Website DetectionCode0
Learning to Propagate for Graph Meta-LearningCode0
GraphCleaner: Detecting Mislabelled Samples in Popular Graph Learning BenchmarksCode0
Fonts-2-Handwriting: A Seed-Augment-Train framework for universal digit classificationCode0
Drone Detection using Deep Neural Networks Trained on Pure Synthetic DataCode0
Icy Moon Surface Simulation and Stereo Depth Estimation for Sampling AutonomyCode0
Dataset Generation and Bonobo Classification from Weakly Labelled VideosCode0
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