DeepAI AI Chat
Log In Sign Up

Guidefill: GPU Accelerated, Artist Guided Geometric Inpainting for 3D Conversion

by   L. Robert Hocking, et al.

The conversion of traditional film into stereo 3D has become an important problem in the past decade. One of the main bottlenecks is a disocclusion step, which in commercial 3D conversion is usually done by teams of artists armed with a toolbox of inpainting algorithms. A current difficulty in this is that most available algorithms are either too slow for interactive use, or provide no intuitive means for users to tweak the output. In this paper we present a new fast inpainting algorithm based on transporting along automatically detected splines, which the user may edit. Our algorithm is implemented on the GPU and fills the inpainting domain in successive shells that adapt their shape on the fly. In order to allocate GPU resources as efficiently as possible, we propose a parallel algorithm to track the inpainting interface as it evolves, ensuring that no resources are wasted on pixels that are not currently being worked on. Theoretical analysis of the time and processor complexiy of our algorithm without and with tracking (as well as numerous numerical experiments) demonstrate the merits of the latter. Our transport mechanism is similar to the one used in coherence transport, but improves upon it by corrected a "kinking" phenomena whereby extrapolated isophotes may bend at the boundary of the inpainting domain. Theoretical results explaining this phenomena and its resolution are presented. Although our method ignores texture, in many cases this is not a problem due to the thin inpainting domains in 3D conversion. Experimental results show that our method can achieve a visual quality that is competitive with the state-of-the-art while maintaining interactive speeds and providing the user with an intuitive interface to tweak the results.


page 13

page 18

page 19

page 31

page 33

page 34

page 35

page 36


NONOTO: A Model-agnostic Web Interface for Interactive Music Composition by Inpainting

Inpainting-based generative modeling allows for stimulating human-machin...

Numerical analysis of shell-based geometric image inpainting algorithms and their semi-implicit extension

In this paper we study a class of fast geometric image inpainting method...

AIM 2020 Challenge on Image Extreme Inpainting

This paper reviews the AIM 2020 challenge on extreme image inpainting. T...

Spectrogram Inpainting for Interactive Generation of Instrument Sounds

Modern approaches to sound synthesis using deep neural networks are hard...

Restore from Restored: Single-image Inpainting

Recent image inpainting methods show promising results due to the power ...

Novel variational model for inpainting in the wavelet domain

Wavelet domain inpainting refers to the process of recovering the missin...

Inpainting in discrete Sobolev spaces: structural information for uncertainty reduction

In this article, using an exemplar-based approach, we investigate the in...