{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T19:03:55Z","timestamp":1782846235051,"version":"3.54.5"},"reference-count":0,"publisher":"ECMS","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,6,23]]},"abstract":"<jats:p>Novel View Synthesis techniques such as 3D Gaussian Splatting (3DGS) conventionally rely on Structure-from-Motion (SfM) to generate the sparse point cloud required for initialisation. SfM, however, fails systematically on textureless or flat surfaces, producing sparse geometry and visible artefacts. This paper presents a synthetic data generation pipeline that bypasses SfM entirely by decoupling geometric and photometric acquisition. A custom path tracing engine employs a toroidal sensor to capture omnidirectional data and produces a dense, ground-truth point cloud that serves as an optimal initialisation state for 3DGS. We investigate several surface sampling strategies and demonstrate that Colour-Based Importance Sampling outperforms uniform methods by concentrating samples on visually informative regions. Experimental results show that our pipeline eliminates the need for Adaptive Density Control, achieves superior reconstruction quality compared to standard SfM-based initialisations, and matches COLMAP training times despite operating on a significantly denser primitive set.<\/jats:p>","DOI":"10.7148\/2026-0762","type":"proceedings-article","created":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T18:08:43Z","timestamp":1782842923000},"page":"762-768","source":"Crossref","is-referenced-by-count":0,"title":["A novel pipeline for 3d gaussian splatting: bridging path tracing and real-time radiance fields"],"prefix":"10.7148","author":[{"given":"Federico","family":"Costantini","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marco Domenico","family":"Buttiglione","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pietro","family":"Piazzolla","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marco","family":"Gribaudo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"4144","published-online":{"date-parts":[[2026,6,23]]},"event":{"name":"40th ECMS International Conference on Modelling and Simulation"},"container-title":["ECMS 2026 Proceedings edited by Filippo Sanfilippo, Florenc Demrozi, Fabio Sgarbossa, Mohammad Poursina"],"original-title":[],"deposited":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T18:08:48Z","timestamp":1782842928000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.scs-europe.net\/dlib\/2026\/ecms2026acceptedpapers\/0762_3dmod_ecms2026_0127.pdf"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,23]]},"references-count":0,"URL":"https:\/\/doi.org\/10.7148\/2026-0762","relation":{},"subject":[],"published":{"date-parts":[[2026,6,23]]}}}