Dynamically estimating light-source-specific parameters for digital images using a neural network

In a digital medium environment for rendering digitally altered scenes, a computer-implemented method for estimating parametric lighting conditions, comprising:

• identifying a request to render a virtual object at a designated position within a digital image;
• extracting a common feature vector from the digital image utilizing common network layers of a source-specific-lighting-estimation-neural network;
• generating, utilizing separate parallel parametric-specific-network layers, a plurality of different three-dimensional (“3D”) source-specific-lighting parameters of a light source illuminating the digital image comprising a first 3D source-specific-lighting parameter of the light source and a second 3D source-specific-lighting parameter of the light source by:
• generating the first 3D source-specific-lighting parameter of the light source by processing the common feature vector from the common network layers utilizing a first parametric-specific-network layer of the source-specific-lighting-estimation-neural network;
• and
• generating the second 3D source-specific-lighting parameter of the light source by processing the common feature vector from the common network layers utilizing a second parametric-specific-network layer of the source-specific-lighting-estimation-neural network, the second parametric-specific-network layer being different than the first parametric-specific-network layer and in parallel with the first parametric-specific-network layer;
• and
• based on the request, rendering a modified digital image comprising the virtual object at the designated position illuminated according to the plurality of different 3D-source-specific-lighting parameters of the light source.

A system comprising:

• one or more memory devices storing a digital image and a source-specific-lighting-estimation-neural network;
• and
• one or more server devices that cause the system to:
• identify a request to render a virtual object at a designated position within the digital image;
• extract a common feature vector from the digital image utilizing common network layers of a source-specific-lighting-estimation-neural network;
• generate, utilizing separate parallel parametric-specific-network layers, a plurality of different three-dimensional (“3D”) source-specific-lighting parameters of a light source illuminating the digital image comprising a first 3D source-specific-lighting parameter of the light source and a second 3D source-specific-lighting parameter of the light source by:
• generating the first 3D source-specific-lighting parameter of the light source by processing the common feature vector from the common network layers utilizing a first parametric-specific-network layer of the source-specific-lighting-estimation-neural network;
• and
• generating the second 3D source-specific-lighting parameter of the light source by processing the common feature vector from the common network layers utilizing a second parametric-specific-network layer of the source-specific-lighting-estimation-neural network, the second parametric-specific-network layer being different than the first parametric-specific-network layer and in parallel with the first parametric-specific-network layer;
• and
• based on the request, render a modified digital image comprising the virtual object at the designated position illuminated according to the plurality of different 3D-source-specific-lighting parameters of the light source.