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Realistically distributing object placements in synthetic training data improves the performance of vision-based object detection models.

Setareh DabiriVasileios LioutasBerend ZwartsenbergYunpeng LiuMatthew NiedobaXiaoxuan LiangDylan GreenJustice SefasJonathan Wilder LavingtonFrank WoodAdam Scibior
Published in: CoRR (2023)
Keyphrases
  • training data
  • object detection
  • classification models
  • real world
  • computer vision
  • test set
  • real time
  • decision trees
  • prior knowledge
  • object segmentation
  • object models
  • background clutter