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 5160 of 308 papers

TitleStatusHype
DCFace: Synthetic Face Generation with Dual Condition Diffusion ModelCode1
CamDiff: Camouflage Image Augmentation via Diffusion ModelCode1
LIQUID: A Framework for List Question Answering Dataset GenerationCode1
ProGen: Progressive Zero-shot Dataset Generation via In-context FeedbackCode1
Scrape, Cut, Paste and Learn: Automated Dataset Generation Applied to Parcel LogisticsCode1
RealFlow: EM-based Realistic Optical Flow Dataset Generation from VideosCode1
HM3D-ABO: A Photo-realistic Dataset for Object-centric Multi-view 3D ReconstructionCode1
Learning to Answer Visual Questions from Web VideosCode1
ZeroGen: Efficient Zero-shot Learning via Dataset GenerationCode1
Detecting Anti-Vaccine Users on TwitterCode1
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