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BEGIN:VEVENT
DTSTAMP:20260417T190100Z
LOCATION:West Building\, Rooms 301-305
DTSTART;TZID=America/Los_Angeles:20250811T140000
DTEND;TZID=America/Los_Angeles:20250811T153000
UID:siggraph_SIGGRAPH 2025_sess110@linklings.com
SUMMARY:Get a Head
DESCRIPTION:Facial Microscopic Structures Synthesis from a Single Unconstr
 ained Image\n\nOur framework can efficiently synthesize facial microstruct
 ure from an unconstrained facial image via differentiable optimization. We
  propose neural wrinkle simulation for differentiable microstructure param
 eterization, and direction distribution similarity to align features with 
 blurry image patche...\n\n\nYouyang Du and Lu Wang (Shandong University) a
 nd Beibei Wang (Nanjing University)\n---------------------\n3DGH: 3D Head 
 Generation with Composable Hair and Face\n\nWe present 3DGH, a generative 
 model that creates realistic 3D human heads with composable hair and face 
 components. By modeling both the separation and correlation between hair a
 nd face in a generative paradigm, it enables high-quality, full-head synth
 esis and flexible 3D hairstyle editing with stro...\n\n\nChengan He (Yale 
 University); Junxuan Li (Meta Codec Avatars Lab); Tobias Kirschstein and A
 rtem Sevastopolskiy (Technical University of Munich); Shunsuke Saito, Qing
 yang Tan, Javier Romero, and Chen Cao (Meta Codec Avatars Lab); Holly Rush
 meier (Yale University); and Giljoo Nam (Meta Codec Avatars Lab)\n--------
 -------------\nText-based Animatable 3D Avatars with Morphable Model Align
 ment\n\nAnimPortrait3D is a novel method for text-based, realistic, animat
 able 3DGS avatar generation with morphable model alignment. To address amb
 iguities in diffusion predictions during 3D distillation, we introduce key
  strategies: initializing a 3D avatar with robust appearance and geometry,
  and leverag...\n\n\nYiqian Wu (ETH Zürich; State Key Lab of CAD and CG, Z
 hejiang University); Malte Prinzler (ETH Zürich); Xiaogang Jin (State Key 
 Lab of CAD and CG, Zhejiang University); and Siyu Tang (ETH Zürich)\n-----
 ----------------\nGet a Head - Interactive Discussion\n\nAfter the summary
  presentations, attendees will participate in an interactive discussion. O
 utside the room will be a series of poster boards for authors to gather ar
 ound with the audience. Authors are invited to bring any material related 
 to their paper that could instigate further conversation such...\n\n------
 ---------------\nSOAP: Style-Omniscient Animatable Portraits\n\nSOAP awake
 ns the 3D princess from 2D stylized photos. Unlike other works that direct
 ly drive the 2D photos, SOAP reconstructs well-rigged 3D avatars, with det
 ailed geometry and all-around texture, from just a single stylized picture
 .\n\n\nTingting Liao and Yujian Zheng (Mohamed bin Zayed University of Art
 ificial Intelligence); Yuliang Xiu (Westlake University); Adilbek Karmanov
  (Mohamed bin Zayed University of Artificial Intelligence); Liwen Hu (Pins
 creen); Leyang Jin (Mohamed bin Zayed University of Artificial Intelligenc
 e); and Hao Li (Mohamed bin Zayed University of Artificial Intelligence, P
 inscreen)\n---------------------\nLAM: Large Avatar Model for One-shot Ani
 matable Gaussian Head\n\nLAM is an innovative Large Avatar Model for anima
 table Gaussian head reconstruction from a single image in seconds. Our Gau
 ssian heads are immediately animatable and renderable without additional n
 etworks or post-processing. This allows seamless integration into existing
  rendering pipelines, ensurin...\n\n\nYisheng He, Xiaodong Gu, Xiaodan Ye,
  Chao Xu, Zhengyi Zhao, Yuan Dong, Weihao Yuan, Zilong Dong, and Liefeng B
 o (Alibaba Group)\n---------------------\nFacial Appearance Capture at Hom
 e with Patch-Level Reflectance Prior\n\nGiven a single co-located smartpho
 ne video captured in a dim room as the input, our method can reconstruct h
 igh-quality facial assets within the distribution modeled by a diffusion p
 rior trained on Light Stage scans, which can be exported to common graphic
 s engines like Blender for photo-realistic r...\n\n\nYuxuan Han and Junfen
 g Lyu (Tsinghua University); Kuan Sheng (ShanghaiTech University; Deemos T
 echnology Co., Ltd.); Minghao Que (Tsinghua University); Qixuan Zhang (Sha
 nghaiTech University; Deemos Technology Co., Ltd.); Lan Xu (ShanghaiTech U
 niversity); and Feng Xu (Tsinghua University)\n\nInterest Area: Research &
  Education\n\nRecording: Livestreamed, Not Livestreamed, Recorded, Not Rec
 orded\n\nRegistration Category: Full Conference, Virtual Access, Monday\n\
 nSession Chair: Ali Mahdavi-Amiri (Simon Fraser University, MARZ VFX)
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