Computational illumination for portrait photography and inverse graphics
Supervised training of deep networks has led to remarkable successes in computer vision, for example on image classification or object detection problems. These successes are driven by the availability of large amounts of paired training data with manual ground truth annotations. For many photograph...
Main Author: | Murmann, Lukas |
---|---|
Other Authors: | Durand, Fredo |
Format: | Thesis |
Published: |
Massachusetts Institute of Technology
2022
|
Online Access: | https://hdl.handle.net/1721.1/139074 |
Similar Items
-
Computational bounce flash for indoor portraits
by: Murmann, Lukas
Published: (2017) -
Computational bounce flash for indoor portraits
by: Murmann, Lukas, et al.
Published: (2021) -
Generative AI Art - portrait photography
by: Ma, Jiaxin
Published: (2024) -
A Dataset of Multi-Illumination Images in the Wild
by: Murmann, Lukas, et al.
Published: (2021) -
Inverse Inverse Graphics
by: Chandra, Kartik
Published: (2023)