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 291300 of 308 papers

TitleStatusHype
E-Gen: Leveraging E-Graphs to Improve Continuous Representations of Symbolic ExpressionsCode0
Drone Detection using Deep Neural Networks Trained on Pure Synthetic DataCode0
Towards Realistic Underwater Dataset Generation and Color RestorationCode0
Bag of Views: An Appearance-based Approach to Next-Best-View Planning for 3D ReconstructionCode0
Neural Network Surrogate and Projected Gradient Descent for Fast and Reliable Finite Element Model Calibration: a Case Study on an Intervertebral DiscCode0
Affordance Learning for End-to-End Visuomotor Robot ControlCode0
Synthetic dataset generation for object-to-model deep learning in industrial applicationsCode0
Towards Synthetic Data Generation for Improved Pain Recognition in Videos under Patient ConstraintsCode0
Dataset Generation and Bonobo Classification from Weakly Labelled VideosCode0
Synthetic Dataset Generation of Driver TelematicsCode0
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