2026-06-06T01:36:03Zhttps://riuma.uma.es/rest/oai/requestoai:riuma.uma.es:10630/247692026-02-03T11:57:05Zcom_10630_2254col_10630_37959
RIUMA. Repositorio Institucional de la Universidad de Málaga
author
Pacheco dos Santos Lima Junior, Marcos Sergio
author
Fernández-Rodríguez, Jose David
author
Ortiz-de-Lazcano-Lobato, Juan Miguel
author
López-Rubio, Ezequiel
author
Domínguez-Merino, Enrique
2022-07-25T11:05:55Z
2022-07-25T11:05:55Z
2022-07
https://hdl.handle.net/10630/24769
Neural rendering is a relatively new field of research that aims to produce high quality perspectives of a 3D scene from a reduced set of sample images. This is done with the help of deep artificial neural networks that model the geometry and color characteristics of the scene. The NeX model relies on neural basis expansion to yield accurate results with a lower computational load than the previous NeRF model. In this work, a procedure is proposed to further enhance the quality of the perspectives generated by NeX. Our proposal is based on the combination of the outputs of several NeX models by a consensus mechanism. The approach is compared to the original NeX for a wide range of scenes. It is found that our method significantly outperforms the original procedure, both in quantitative and qualitative terms.
eng
Redes neuronales (Informática) - Congresos
Aprendizaje automático (Inteligencia artificial) - Congresos
Sistemas autoorganizativos - Congresos
Enhanced Perspective Generation by Consensus of NeX neural models
conference output
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URL
https://riuma.uma.es/bitstreams/c541569e-0c97-454d-9cf4-f0a0e4c06ff0/download
File
MD5
cf053dbe74dd502949bdd86fffb03e1a
864554
application/pdf
PreprintMini.pdf