Ya-Liang Chang — accepted AI-conference papers

2020

GDN: A Coarse-To-Fine (C2F) Representation for End-To-End 6-DoF Grasp Detection

Kuang-Yu Jeng, Yueh-Cheng Liu, Zhe Yu Liu, Jen-Wei Wang, Ya-Liang Chang, Hung-Ting Su +1

CoRL 2020

We proposed an end-to-end grasp detection network, Grasp Detection Network (GDN), cooperated with a novel coarse-to-fine (C2F) grasp representation design to detect diverse and accurate 6-DoF grasps based on point clouds. Compared to previous two-stage approaches which sample and evaluate multiple g

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2019

Free-Form Video Inpainting With 3D Gated Convolution and Temporal PatchGAN

Ya-Liang Chang, Zhe Yu Liu, Kuan-Ying Lee, Winston Hsu

ICCV 2019poster

Free-form video inpainting is a very challenging task that could be widely used for video editing such as text removal. Existing patch-based methods could not handle non-repetitive structures such as faces, while directly applying image-based inpainting models to videos will result in temporal incon…

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