Pre-recorded Sessions: From 4 December 2020 | Live Sessions: 10 – 13 December 2020
4 – 13 December 2020
Q&A for FeatureNet: Upsampling of Point Cloud and it’s Associated Features
src="/
-
Ultimate Supporter
src="/
-
Ultimate Attendee
src="/
-
Basic Attendee
Date:
Time: -
Venue:
Session Chair:
Note: All live sessions will be screened on Singapore Time/GMT+8. Convert your time zone here.
Q&A for FeatureNet: Upsampling of Point Cloud and it’s Associated Features
Author(s)/Presenter(s):
Shanthika Naik, KLE Technological University, India
Uma Mudenagudi, KLE Technological University, India
Ramesh Tabib, KLE Technological University, India
Adarsh Jamadandi, KLE Technological University, India
Abstract: The paper presents a deep learning architecture to upsample vertices and it's associated features and a novel feature loss function designed for accommodating training of both vertex and associated features.