Learning to Predict Scene-Level Implicit 3D from Posed RGBD Data

Autor:	Kulkarni, Nilesh, Jin, Linyi, Johnson, Justin, Fouhey, David F.
Rok vydání:	2023
Předmět:	Computer Science - Computer Vision and Pattern Recognition
Druh dokumentu:	Working Paper
Popis:	We introduce a method that can learn to predict scene-level implicit functions for 3D reconstruction from posed RGBD data. At test time, our system maps a previously unseen RGB image to a 3D reconstruction of a scene via implicit functions. While implicit functions for 3D reconstruction have often been tied to meshes, we show that we can train one using only a set of posed RGBD images. This setting may help 3D reconstruction unlock the sea of accelerometer+RGBD data that is coming with new phones. Our system, D2-DRDF, can match and sometimes outperform current methods that use mesh supervision and shows better robustness to sparse data. Comment: Project page this https://nileshkulkarni.github.io/d2drdf/
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2306.08671 Zobrazit plný text záznamu View this record from Arxiv