Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Chun Wei Ooi"'
Publikováno v:
2023 IEEE Conference Virtual Reality and 3D User Interfaces (VR).
Autor:
Chun Wei Ooi, John Dingliana
Publikováno v:
SIGGRAPH Asia 2022 Posters.
Autor:
Chun Wei Ooi, John Dingliana
Publikováno v:
SIGGRAPH Asia Posters
Autor:
Shohei Ikawa, Tomoyoshi Ito, Yuki Maeda, Hiroaki Niwase, Tomoyoshi Shimobaba, Chun Wei Ooi, Masato Fujiwara, Takashi Kakue, Hiromitsu Araki, Naoki Takada
Publikováno v:
Chinese Optics Letters. 15:060901-60904
We propose a simple gradation representation method using a binary-weighted computer-generated hologram (CGH) to be displayed on a high-speed spatial light modulator that can be controlled by the pulse-width modulation technique. The proposed method
Autor:
Takashi Kakue, Yuki Maeda, Chun Wei Ooi, Tomoyoshi Ito, Tomoyoshi Shimobaba, Hirotaka Nakayama, Masato Fujiwara, Naoki Takada
Publikováno v:
IEICE Transactions on Electronics. :978-983
Publikováno v:
AH
Machine learning have been recently applied to multiple areas, including fashion. Fashion design by generated images makes it possible to inherit design without fashion designer and get inspiration, however, little research has been done on usage of
Publikováno v:
SIGGRAPH Asia Technical Briefs
We present a design and rendering method for large eye-box, fully parallax, depth of field included near-eye augmented reality (AR) display. As developments in AR progress, field of view and sense of depth are one of the most crucial factors for rend
Autor:
Maniprakash Balasubramanian, Chaitanaya Desai, Sheikna Kulam, Chun Wei Ooi, Rakesh Rajagopal, Clement Sanjivi, Andreas Tan
Whether you're upgrading an existing billing system or moving to a subscription- or consumption-based model, SAP BRIM is ready—and here's is your guide! From subscription order management and charging to invoicing and contract accounting, get step-
Publikováno v:
SIGGRAPH ASIA (Posters)
Three-dimensions (3D) models contain a wealth of information about every object in our universe. However, it is difficult to semantically recognize the media forms, even when they featured in simplest form of objects. We propose the DeepHolo network