Search Results for author: Inyoung Lee

Found 3 papers, 2 papers with code

DiffRef3D: A Diffusion-based Proposal Refinement Framework for 3D Object Detection

no code implementations25 Oct 2023 Se-Ho Kim, Inyong Koo, Inyoung Lee, Byeongjun Park, Changick Kim

During training, DiffRef3D gradually adds noise to the residuals between proposals and target objects, then applies the noisy residuals to proposals to generate hypotheses.

3D Object Detection Denoising +2

PG-RCNN: Semantic Surface Point Generation for 3D Object Detection

1 code implementation ICCV 2023 Inyong Koo, Inyoung Lee, Se-Ho Kim, Hee-Seon Kim, Woo-jin Jeon, Changick Kim

Motivated by this, we propose Point Generation R-CNN (PG-RCNN), a novel end-to-end detector that generates semantic surface points of foreground objects for accurate detection.

3D Object Detection object-detection +1

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