1 code implementation • 20 Jul 2020 • Shih-Hung Liu, Shang-Yi Yu, Shao-Chi Wu, Hwann-Tzong Chen, Tyng-Luh Liu
This paper presents a novel method for instance segmentation of 3D point clouds.
Ranked #9 on 3D Instance Segmentation on S3DIS (mPrec metric)
no code implementations • 28 Dec 2019 • Kuo-Wei Lee, Shih-Hung Liu, Hwann-Tzong Chen, Koichi Ito
3D hand pose estimation has received a lot of attention for its wide range of applications and has made great progress owing to the development of deep learning.
no code implementations • COLING 2016 • Kuan-Yu Chen, Shih-Hung Liu, Berlin Chen, Hsin-Min Wang
The D-EV model not only inherits the advantages of the EV model but also can infer a more robust representation for a given spoken paragraph against imperfect speech recognition.
no code implementations • 22 Jul 2016 • Kuan-Yu Chen, Shih-Hung Liu, Berlin Chen, Hsin-Min Wang, Hsin-Hsi Chen
Word embedding methods revolve around learning continuous distributed vector representations of words with neural networks, which can capture semantic and/or syntactic cues, and in turn be used to induce similarity measures among words, sentences and documents in context.
no code implementations • 20 Jan 2016 • Kuan-Yu Chen, Shih-Hung Liu, Berlin Chen, Hsin-Min Wang
In addition to MMR, there is only a dearth of research concentrating on reducing redundancy or increasing diversity for the spoken document summarization task, as far as we are aware.
no code implementations • 14 Jun 2015 • Kuan-Yu Chen, Shih-Hung Liu, Hsin-Min Wang, Berlin Chen, Hsin-Hsi Chen
Owing to the rapidly growing multimedia content available on the Internet, extractive spoken document summarization, with the purpose of automatically selecting a set of representative sentences from a spoken document to concisely express the most important theme of the document, has been an active area of research and experimentation.