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TZID:Asia/Seoul
X-LIC-LOCATION:Asia/Seoul
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TZOFFSETTO:+0900
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DTSTART:18871231T000000
DTSTART:19881009T020000
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BEGIN:VEVENT
DTSTAMP:20230103T035347Z
LOCATION:Room 325-AB\, Level 3\, West Wing
DTSTART;TZID=Asia/Seoul:20221207T140000
DTEND;TZID=Asia/Seoul:20221207T153000
UID:siggraphasia_SIGGRAPH Asia 2022_sess162@linklings.com
SUMMARY:Face, Speech, and Gesture
DESCRIPTION:Technical Communications, Technical Papers\n\nThe presentation
 s will be followed by a 30-min Interactive Discussion Session at Room 325-
 CD.\n\nThe Technical Papers program is the premier international forum for
  disseminating new scholarly work in computer graphics and interactive tec
 hniques. Technical Papers are published as a special issue of ACM Transact
 ions on Graphics. In addition to papers selected by the SIGGRAPH Asia 2022
  Technical Papers Jury, the conference presents papers that have been publ
 ished in ACM Transactions on Graphics during the past year. Accepted paper
 s adhere to the highest scientific standards.\n\nThe Technical Communicati
 ons program is a premier forum for presenting the latest developments and 
 research still in progress. Leading international experts in academia and 
 industry present work that showcase actual implementations of research ide
 as, works at the crossroads of computer graphics with computer vision, mac
 hine learning, HCI, VR, CAD, visualization, and many others\n\nAnimatomy: 
 an Animator-centric, Anatomically Inspired System for 3D Facial Modeling, 
 Animation and Transfer\n\nChoi, Eom, Mouscadet, Cullingford, Ma...\n\nWe p
 resent Animatomy, a novel anatomic+animator centric representation of the 
 human face. Present FACS-based systems are plagued with problems of face m
 uscle separation, coverage, opposition, and redundancy. We, therefore, pro
 pose a collection of muscle fiber curves as an anatomic basis, whose contr
 ...\n\n---------------------\nPADL: Language-Directed Physics-Based Charac
 ter Control\n\nJuravsky, Guo, Fidler, Peng\n\nDeveloping systems that can 
 synthesize natural and life-like motions for simulated characters has long
  been a focus for computer animation. But in order for these systems to be
  useful for downstream applications, they need not only produce high-quali
 ty motions, but must also provide an accessible an...\n\n-----------------
 ----\nMasked Lip-Sync Prediction by Audio-Visual Contextual Exploitation i
 n Transformers\n\nSun, Zhou, Wang, Wu, Hong...\n\nPrevious studies have ex
 plored generating accurately lip-synced talking faces for arbitrary target
 s given audio conditions. However, most of them deform or generate the who
 le facial area, leading to non-realistic results. In this work, we delve i
 nto the formulation of altering only the mouth shapes ...\n\n-------------
 --------\nRhythmic Gesticulator: Rhythm-Aware Co-Speech Gesture Synthesis 
 with Hierarchical Neural Embeddings\n\nAo, Gao, Lou, Chen, Liu\n\nAutomati
 c synthesis of realistic co-speech gestures is an increasingly important y
 et challenging task in artificial embodied agent creation. Previous system
 s mainly focus on generating gestures in an end-to-end manner, which leads
  to difficulties in mining the clear rhythm and semantics due to the c...\
 n\n---------------------\nTowards Virtual Humans without Gender Stereotype
 d Visual Features\n\nAraujo, Schaffer, Costa, Musse\n\nTo assess gender bi
 as towards a simulated baby, our research indicates that simply reporting 
 gender may be sufficient to create a perception of gender that affects the
  participant's emotional response.\n\n---------------------\nVOCAL: Vowel 
 and Consonant Layering for Expressive  Animator-Centric Singing Animation\
 n\nPan, Landreth, Fiume, Singh\n\nSinging and speaking are two fundamental
  forms of human communication. From a modeling perspective however, speaki
 ng can be seen as a subset of singing. We present VOCAL, a system that aut
 omatically generates expressive, animator-centric lower face animation fro
 m singing audio input. Articulatory ph...\n\n---------------------\nVideo-
 driven Neural Physically-based Facial Asset for Production\n\nZhang, Zeng,
  Zhang, Lin, Cao...\n\nProduction-level workflows for producing convincing
  3D dynamic human faces have long relied on an assortment of labor-intensi
 ve tools for geometry and texture generation, motion capture and rigging, 
 and expression synthesis. Recent neural approaches automate individual com
 ponents but the correspondi...\n\n\nRegistration Category: FULL ACCESS, ON
 -DEMAND ACCESS\n\nLanguage: ENGLISH\n\nFormat: IN-PERSON, ON-DEMAND
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