公开(公告)号：US20200342263A1

公开(公告)日：2020-10-29

申请号：US16924005

申请日：2020-07-08

Applicant: NVIDIA Corporation

Inventor： Orazio Gallo ,  Jinwei Gu ,  Jan Kautz ,  Patrick Wieschollek

IPC: G06K9/62

Abstract: When a computer image is generated from a real-world scene having a semi-reflective surface (e.g. window), the computer image will create, at the semi-reflective surface from the viewpoint of the camera, both a reflection of a scene in front of the semi-reflective surface and a transmission of a scene located behind the semi-reflective surface. Similar to a person viewing the real-world scene from different locations, angles, etc., the reflection and transmission may change, and also move relative to each other, as the viewpoint of the camera changes. Unfortunately, the dynamic nature of the reflection and transmission negatively impacts the performance of many computer applications, but performance can generally be improved if the reflection and transmission are separated. The present disclosure uses deep learning to separate reflection and transmission at a semi-reflective surface of a computer image generated from a real-world scene.

公开(公告)号：US10762620B2

公开(公告)日：2020-09-01

申请号：US16200192

申请日：2018-11-26

Applicant: NVIDIA Corporation

Inventor： Orazio Gallo ,  Jinwei Gu ,  Jan Kautz ,  Patrick Wieschollek

IPC: G06T7/00 ,  G06K9/62 ,  G06T1/20 ,  G06N20/00 ,  G06T11/40 ,  G06T15/00 ,  G06T5/00

Abstract: When a computer image is generated from a real-world scene having a semi-reflective surface (e.g. window), the computer image will create, at the semi-reflective surface from the viewpoint of the camera, both a reflection of a scene in front of the semi-reflective surface and a transmission of a scene located behind the semi-reflective surface. Similar to a person viewing the real-world scene from different locations, angles, etc., the reflection and transmission may change, and also move relative to each other, as the viewpoint of the camera changes. Unfortunately, the dynamic nature of the reflection and transmission negatively impacts the performance of many computer applications, but performance can generally be improved if the reflection and transmission are separated. The present disclosure uses deep learning to separate reflection and transmission at a semi-reflective surface of a computer image generated from a real-world scene.

公开(公告)号：US20190164268A1

公开(公告)日：2019-05-30

申请号：US16200192

申请日：2018-11-26

Applicant: NVIDIA Corporation

Inventor： Orazio Gallo ,  Jinwei Gu ,  Jan Kautz ,  Patrick Wieschollek

IPC: G06T7/00 ,  G06K9/62 ,  G06T1/20 ,  G06T11/40 ,  G06N20/00

Abstract: When a computer image is generated from a real-world scene having a semi-reflective surface (e.g. window), the computer image will create, at the semi-reflective surface from the viewpoint of the camera, both a reflection of a scene in front of the semi-reflective surface and a transmission of a scene located behind the semi-reflective surface. Similar to a person viewing the real-world scene from different locations, angles, etc., the reflection and transmission may change, and also move relative to each other, as the viewpoint of the camera changes. Unfortunately, the dynamic nature of the reflection and transmission negatively impacts the performance of many computer applications, but performance can generally be improved if the reflection and transmission are separated. The present disclosure uses deep learning to separate reflection and transmission at a semi-reflective surface of a computer image generated from a real-world scene.

公开(公告)号：US11270161B2

公开(公告)日：2022-03-08

申请号：US16924005

申请日：2020-07-08

Applicant: NVIDIA Corporation

Inventor： Orazio Gallo ,  Jinwei Gu ,  Jan Kautz ,  Patrick Wieschollek

IPC: G06K9/00 ,  G06K9/62

Abstract: When a computer image is generated from a real-world scene having a semi-reflective surface (e.g. window), the computer image will create, at the semi-reflective surface from the viewpoint of the camera, both a reflection of a scene in front of the semi-reflective surface and a transmission of a scene located behind the semi-reflective surface. Similar to a person viewing the real-world scene from different locations, angles, etc., the reflection and transmission may change, and also move relative to each other, as the viewpoint of the camera changes. Unfortunately, the dynamic nature of the reflection and transmission negatively impacts the performance of many computer applications, but performance can generally be improved if the reflection and transmission are separated. The present disclosure uses deep learning to separate reflection and transmission at a semi-reflective surface of a computer image generated from a real-world scene.