Název:	Reflection probe interpolation for fast and accurate rendering of reflective materials
Autoři:	Gojoković, Katarina Lesar, Žiga Marolt, Matija
Citace zdrojového dokumentu:	Journal of WSCG. 2024, vol. 32, no. 1-2, p. 81-70.
Datum vydání:	2024
Nakladatel:	Václav Skala - UNION Agency
Typ dokumentu:	článek article
URI:	http://hdl.handle.net/11025/57345
ISSN:	1213 – 6972 1213 – 6980 (CD-ROM) 1213 – 6964 (on-line)
Klíčová slova:	odrazové sondy;interpolace;konvoluční neuronové sítě
Klíčová slova v dalším jazyce:	reflection probes;interpolation;convolutional neural networks
Abstrakt v dalším jazyce:	In this paper, we aim to improve rendering reflections using environment maps on moving reflective objects. Such scenarios require multiple reflection probes to be positioned at various locations in a scene. During rendering, the closest reflection probe is typically chosen as the environment map of a specific object, resulting in sharp transitions between the rendered reflections when the object moves around the scene. To solve this problem, we developed two convolutional neural networks that dynamically synthesize the best possible environment map at a given point in the scene. The first network generates an environment map from the coordinates of a given point through a decoder architecture. In the second approach, we triangulated the scene and captured environment maps at the triangle vertices – these represent reflection probes. The second network receives at the input three environment maps captured at the vertices of the triangle containing the query point, along with the distances between the query point and the vertices. Through an encoder-decoder architecture, the second network performs smart interpolation of the three environment maps. Both approaches are based on the phenomenon of overfitting, which made it necessary to train each network individually for specific scenes. Both networks are successful at predicting environment maps at arbitrary locations in the scene, even if these locations were not part of the training set. The accuracy of the predictions strongly depends on the complexity of the scene itself.
Práva:	© Václav Skala - UNION Agency © Václav Skala - UNION Agency
Vyskytuje se v kolekcích:	Volume 32, number 1-2 (2024)

Všechny záznamy v DSpace jsou chráněny autorskými právy, všechna práva vyhrazena.