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PRODID:Linklings LLC
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TZID:Asia/Seoul
X-LIC-LOCATION:Asia/Seoul
BEGIN:STANDARD
TZOFFSETFROM:+0900
TZOFFSETTO:+0900
TZNAME:KST
DTSTART:18871231T000000
DTSTART:19881009T020000
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BEGIN:VEVENT
DTSTAMP:20230103T035348Z
LOCATION:Room 324\, Level 3\, West Wing
DTSTART;TZID=Asia/Seoul:20221209T140000
DTEND;TZID=Asia/Seoul:20221209T153000
UID:siggraphasia_SIGGRAPH Asia 2022_sess174@linklings.com
SUMMARY:Material and Rendering
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\nLook-Ahead
  Training with Learned Reflectance Loss for Single-Image SVBRDF Estimation
 \n\nZhou, Kalantari\n\nIn this paper, we propose a novel optimization-base
 d method to estimate the reflectance properties of a near planar surface f
 rom a single input image. Specifically, we perform test-time optimization 
 by directly updating the parameters of a neural network to minimize the te
 st error. Since single imag...\n\n---------------------\nConstant Time Med
 ian Filter using 2D Wavelet Matrix\n\nMoroto, Umetani\n\nThe median filter
  is a simple yet powerful noise reduction technique that is extensively ap
 plied in image, signal, and speech processing. It can effectively remove i
 mpulsive noise while preserving the content of the image by taking the med
 ian of neighboring pixels; thus, it has various applications,...\n\n------
 ---------------\nComputational Alternative Photographic Process toward Sus
 tainable Printing\n\nOzawa, Yamamoto, Izumi, Ochiai\n\nWe propose a comput
 ational alternative photographic process that integrates computer processi
 ng with the conventional printing method, particularly cyanotype.\n\n-----
 ----------------\nDirect acquisition of volumetric scattering phase functi
 on using speckle correlations\n\nAlterman, Saiko, Levin\n\nIn material acq
 uisition we want to infer the internal properties of materials  from the w
 ay they scatter light.  In particular, we are interested in measuring the 
 phase function of the material, governing the amount of energy scattered t
 owards different directions.  This phase function has been show...\n\n----
 -----------------\nVIINTER: View Interpolation With Implicit Neural Repres
 entations of Images\n\nFeng, Jabbireddy, Varshney\n\nWe present VIINTER, a
  method for view interpolation by interpolating the implicit neural repres
 entation (INR) of the captured images. We leverage the learned code vector
  associated with each image and interpolate between these codes to achieve
  viewpoint transitions. We propose several techniques tha...\n\n----------
 -----------\nFloRen: Real-time High-quality Human Performance Rendering vi
 a Appearance Flow Using Sparse RGB Cameras\n\nShao, Chen, Zheng, Zhang, Zh
 ang...\n\nWe propose FloRen, a novel system for real-time, high-resolution
  free-view human synthesis. Our system runs at 15fps in 1K resolution with
  very sparse RGB cameras. In FloRen, a coarse-level implicit geometry is r
 ecovered at first as initialization, and then processed by a neural render
 ing framework ...\n\n---------------------\nProgressive Material Caching\n
 \nFujieda, Harada\n\nWe introduce an efficient method to evaluate material
 s by progressively caching them without an overhead. A fixed-size hash tab
 le is used to store and lookup them effectively on the GPU.\n\n\nRegistrat
 ion Category: FULL ACCESS, ON-DEMAND ACCESS\n\nLanguage: ENGLISH\n\nFormat
 : IN-PERSON, ON-DEMAND
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