BEGIN:VCALENDAR
VERSION:2.0
PRODID:Linklings LLC
BEGIN:VTIMEZONE
TZID:Australia/Melbourne
X-LIC-LOCATION:Australia/Melbourne
BEGIN:DAYLIGHT
TZOFFSETFROM:+1000
TZOFFSETTO:+1100
TZNAME:AEDT
DTSTART:19721003T020000
RRULE:FREQ=YEARLY;BYMONTH=4;BYDAY=1SU
END:DAYLIGHT
BEGIN:STANDARD
DTSTART:19721003T020000
TZOFFSETFROM:+1100
TZOFFSETTO:+1000
TZNAME:AEST
RRULE:FREQ=YEARLY;BYMONTH=10;BYDAY=1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20260114T163659Z
LOCATION:Meeting Room C4.8\, Level 4 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231215T131500
DTEND;TZID=Australia/Melbourne:20231215T141000
UID:siggraphasia_SIGGRAPH Asia 2023_sess157@linklings.com
SUMMARY:Put Things Together
DESCRIPTION:Neural Packing: from Visual Sensing to Reinforcement Learning\
 n\nWe present a novel learning framework to solve the transport-and-packin
 g (TAP) problem in 3D. It constitutes a full solution pipeline from partia
 l observations of input objects via RGBD sensing and recognition to final 
 box placement, via robotic motion planning, to arrive at a compact packing
  in a t...\n\n\nJuzhan Xu (Shenzhen University), Minglun Gong (University 
 of Guelph), Hao Zhang (Simon Fraser University), and Hui Huang and Ruizhen
  Hu (Shenzhen University)\n---------------------\nReconstruction of Machin
 e-Made Shapes from Bitmap Sketches\n\nWe propose a method of reconstructin
 g 3D machine-made shapes from bitmap sketches by separating an input image
  into individual patches and jointly optimizing their geometry. \nWe rely 
 on two main observations:\n(1) human observers interpret sketches of man-m
 ade shapes as a collection of simple geometr...\n\n\nIvan Puhachov (Univer
 site de Montreal; Huawei Technologies, Canada); Cedric Martens (Universite
  de Montreal); Paul G. Kry (McGill University; Huawei Technologies, Canada
 ); and Mikhail Bessmeltsev (Universite de Montreal)\n---------------------
 \nLearning based 2D Irregular Shape Packing\n\n2D irregular shape packing 
 is a necessary step to arrange UV patches of a 3D model within a texture a
 tlas for memory-efficient appearance rendering in computer graphics. Being
  a joint, combinatorial decision-making problem involving all patch positi
 ons and orientations, this problem has well-known N...\n\n\nZeshi Yang and
  Zherong Pan (Tencent America), Manyi Li (Shandong University), and Kui Wu
  and Xifeng Gao (Tencent America)\n---------------------\nLearning Gradien
 t Fields for Scalable and Generalizable Irregular Packing\n\nThe packing p
 roblem, also known as cutting or nesting, has diverse applications in logi
 stics, manufacturing, layout design, and atlas generation. It involves arr
 anging irregularly shaped pieces to minimize waste while avoiding overlap.
  Recent advances in machine learning, particularly reinforcement ...\n\n\n
 Tianyang Xue (Shandong University), Mingdong Wu (Peking University), Lin L
 u and Haoxuan Wang (Shandong University), and Hao Dong and Baoquan Chen (P
 eking University)\n\nRegistration Category: Full Access\n\nSession Chair: 
 Chi Wing Fu (The Chinese University of Hong Kong)
END:VEVENT
END:VCALENDAR