BEGIN:VCALENDAR VERSION:2.0 PRODID:Linklings LLC BEGIN:VTIMEZONE TZID:Asia/Tokyo X-LIC-LOCATION:Asia/Tokyo BEGIN:STANDARD TZOFFSETFROM:+0900 TZOFFSETTO:+0900 TZNAME:JST DTSTART:18871231T000000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20250110T023312Z LOCATION:Hall B5 (2)\, B Block\, Level 5 DTSTART;TZID=Asia/Tokyo:20241204T113100 DTEND;TZID=Asia/Tokyo:20241204T114300 UID:siggraphasia_SIGGRAPH Asia 2024_sess113_papers_847@linklings.com SUMMARY:Neural Light Spheres for Implicit Image Stitching and View Synthes is DESCRIPTION:Technical Papers\n\nIlya Chugunov and Amogh Joshi (Princeton U niversity), Kiran Murthy and Francois Bleibel (Google Inc.), and Felix Hei de (Princeton University)\n\nChallenging to capture, and challenging to di splay on a cellphone screen, the panorama paradoxically remains both a sta ple and underused feature of modern mobile camera applications. In this wo rk we address both of these challenges with a spherical neural light field model for implicit panoramic image stitching and re-rendering; able to ac commodate for depth parallax, view-dependent lighting, and local scene mot ion and color changes during capture. Fit during test-time to an arbitrary path panoramic video capture -- vertical, horizontal, random-walk -- thes e neural light spheres jointly estimate the camera path and a high-resolut ion scene reconstruction to produce novel wide field-of-view projections o f the environment. Our single-layer model avoids expensive volumetric samp ling, and decomposes the scene into compact view-dependent ray offset and color components, with a total model size of 80 MB per scene, and real-tim e (50 FPS) rendering at 1080p resolution. We demonstrate improved reconstr uction quality over traditional image stitching and radiance field methods , with significantly higher tolerance to scene motion and non-ideal captur e settings.\n\nRegistration Category: Full Access, Full Access Supporter\n \nLanguage Format: English Language\n\nSession Chair: Forrester Cole (Goog le) URL:https://asia.siggraph.org/2024/program/?id=papers_847&sess=sess113 END:VEVENT END:VCALENDAR