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 191200 of 308 papers

TitleStatusHype
Prompt2Model: Generating Deployable Models from Natural Language InstructionsCode4
DatasetDM: Synthesizing Data with Perception Annotations Using Diffusion ModelsCode2
Labeling without Seeing? Blind Annotation for Privacy-Preserving Entity Resolution0
Around the GLOBE: Numerical Aggregation Question-Answering on Heterogeneous Genealogical Knowledge Graphs with Deep Neural Networks0
Supervised Homography Learning with Realistic Dataset GenerationCode1
SynTable: A Synthetic Data Generation Pipeline for Unseen Object Amodal Instance Segmentation of Cluttered Tabletop ScenesCode1
Bag of Views: An Appearance-based Approach to Next-Best-View Planning for 3D ReconstructionCode0
Mitosis Detection from Partial Annotation by Dataset Generation via Frame-Order FlippingCode0
The Big Data Myth: Using Diffusion Models for Dataset Generation to Train Deep Detection Models0
NeuroGraph: Benchmarks for Graph Machine Learning in Brain ConnectomicsCode1
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