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:20260114T163633Z LOCATION:Darling Harbour Theatre\, Level 2 (Convention Centre) DTSTART;TZID=Australia/Melbourne:20231212T093000 DTEND;TZID=Australia/Melbourne:20231212T124500 UID:siggraphasia_SIGGRAPH Asia 2023_sess209_papers_820@linklings.com SUMMARY:Transparent Object Reconstruction via Implicit Differentiable Refr action Rendering DESCRIPTION:Fangzhou Gao, Lianghao Zhang, Li Wang, Jiamin Cheng, and Jiawa n Zhang (Tianjin University)\n\nReconstructing the geometry of transparent objects has been a long-standing challenge. Existing methods rely on comp lex setups, such as manual annotation or darkroom conditions, to obtain ob ject silhouettes and usually require controlled environments with designed patterns to infer ray-background correspondence. However, these intricate arrangements limit the practical application for common users. In this pa per, we significantly simplify the setups and present a novel method that reconstructs transparent objects in unknown natural scenes without manual assistance. Our method incorporates two key technologies. Firstly, we intr oduce a volume rendering-based method that estimates object silhouettes by projecting the 3D neural field onto 2D images. This automated process yie lds highly accurate multi-view object silhouettes from images captured in natural scenes. Secondly, we propose transparent object optimization throu gh differentiable refraction rendering with the neural SDF field, enabling us to optimize the refraction ray based on color rather than explicit ray -background correspondence. Additionally, our optimization includes a ray sampling method to supervise the object silhouette at a low computational cost. Extensive experiments and comparisons demonstrate that our method pr oduces high-quality results while offering much more convenient setups.\n\ nRegistration Category: Full Access, Enhanced Access, Trade Exhibitor, Exp erience Hall Exhibitor\n\n URL:https://asia.siggraph.org/2023/full-program?id=papers_820&sess=sess209 END:VEVENT END:VCALENDAR