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Jae Joong Lee

2 accepted papers

2026

Tuning-Free Amodal Segmentation via the Occlusion-Free Bias of Inpainting Models

AAAI 2026technical

Amodal segmentation is an image-based algorithm that aims to predict masks for both visible and occluded parts of objects. Existing methods typically rely on supervised learning with annotated amodal masks or synthetic data. The effectiveness of these methods relies heavily on the quality of the dat

Cited by 0SourcePDFScholar
2024

Tree-D Fusion: Simulation-Ready Tree Dataset from Single Images with Diffusion Priors

ECCV 2024poster

"We introduce , featuring the first collection of 600,000 environmentally aware, 3D simulation-ready tree models generated through Diffusion priors. Each reconstructed 3D tree model corresponds to an image from Google’s Auto Arborist Dataset, comprising street view images and associated genus labels…

Cited by 4SourcePDFScholar