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TZID:Asia/Tokyo
X-LIC-LOCATION:Asia/Tokyo
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BEGIN:VEVENT
DTSTAMP:20260817T171539Z
LOCATION:Hall B7 (1)\, B Block\, Level 7
DTSTART;TZID=Asia/Tokyo:20241203T144500
DTEND;TZID=Asia/Tokyo:20241203T155500
UID:siggraphasia_SIGGRAPH Asia 2024_sess108@linklings.com
SUMMARY:Design It All: Font, Paint, and Colors
DESCRIPTION:Each Paper gives a 10 minute presentation.\n\nHFH-Font: Few-sh
 ot Chinese Font Synthesis with Higher Quality, Faster Speed, and Higher Re
 solution\n\nThe challenge of automatically synthesizing high-quality vecto
 r fonts, particularly for writing systems (e.g., Chinese) consisting of hu
 ge amounts of complex glyphs, remains unsolved. Existing font synthesis te
 chniques fall into two categories: 1) methods that directly generate vecto
 r glyphs, and 2)...\n\n\nHua Li (Wangxuan Institute of Computer Technology
 , Peking University) and Zhouhui Lian (Wangxuan Institute of Computer Tech
 nology, Peking University; State Key Laboratory of General Artificial Inte
 lligence, Peking University)\n---------------------\nSD-𝜋XL: Generating Lo
 w-Resolution Quantized Imagery via Score Distillation\n\nLow-resolution qu
 antized imagery, such as pixel art, is seeing a revival in modern applicat
 ions ranging from video game graphics to digital design and fabrication, w
 here creativity is often bound by a limited palette of elemental units. De
 spite their growing popularity, the automated generation of q...\n\n\nAlex
 andre Binninger and Olga Sorkine-Hornung (ETH Zürich)\n-------------------
 --\nProcessPainter: Learning to draw from sequence data\n\nThe painting pr
 ocess of artists is inherently stepwise and varies significantly among dif
 ferent painters and styles. Generating detailed, step-by-step painting pro
 cesses is essential for art education and research, yet remains largely un
 derexplored. Traditional stroke-based rendering methods break d...\n\n\nYi
 ren Song (National University of Singapore, Show Lab); Shijie Huang, Chen 
 Yao, and Hai Ci (National University of Singapore); Xiaojun Ye (Zhejiang U
 niversity); Jiaming Liu (Tiamat); Yuxuan Zhang (Shanghai Jiao Tong Univers
 ity); and Mike Zheng Shou (National University of Singapore)\n------------
 ---------\nInverse Painting: Reconstructing The Painting Process\n\nGiven 
 an input painting, we reconstruct a time-lapse video of how it may be pain
 ted.  We formulate this as an autoregressive image generation problem, in 
 which an initially blank "canvas'' is iteratively updated. The model learn
 s from real artists by training on many painting videos.\nOur approach in.
 ..\n\n\nBowei Chen, Yifan Wang, Brian Curless, Ira Kemelmacher-Shlizerman,
  and Steven M. Seitz (University of Washington)\n---------------------\nLV
 CD: Reference-based Lineart Video Colorization with Diffusion Models\n\nWe
  propose the first video diffusion framework for reference-based lineart v
 ideo colorization. Unlike previous works that rely solely on image generat
 ive models to colorize lineart frame by frame, our approach leverages a la
 rge-scale pretrained video diffusion model to generate colorized animation
  v...\n\n\nZhitong Huang (City University of Hong Kong); Mohan Zhang (Wech
 at, Tencent Inc.); and Jing Liao (City University of Hong Kong)\n---------
 ------------\nColorful Diffuse Intrinsic Image Decomposition in the Wild\n
 \nIntrinsic image decomposition aims to separate the surface reflectance a
 nd the effects from the illumination given a single photograph. Due to the
  complexity of the problem, most prior works assume a single-color illumin
 ation and a Lambertian world, which limits their use in illumination-aware
  image...\n\n\nChris Careaga and Yağız Aksoy (Simon Fraser University)\n\n
 Registration Category: Full Access, Full Access Supporter\n\nLanguage Form
 at: English Language\n\nSession Chair: I-Chao Shen (The University of Toky
 o)
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