Furkan Kınlı

Furkan Kınlı

Ph.D. Candidate
Computer Science
Özyeğin University

Re: VCNet: A Robust Approach to Blind Image Inpainting

ML Reproducibility Challenge 2020

Abstract

In this study, we report and reproduce, on a large scale, the results of the article of a novel blind image inpainting architecture, namely VCNet, which jointly-controls the mask prediction and the blind inpainting modules. We have implemented this architecture from scratch in PyTorch, and then have conducted our experiments and blind inpainting evaluation on all datasets, as described in the article. We have achieved to reproduce the results qualitatively and quantitatively in most cases.

Report | Code

Bibtex:

@misc{
        k{\i}nl{\i}2021re,
        title={[Re] {VCN}et: A Robust Approach to Blind Image Inpainting},
        author={Furkan K{\i}nl{\i} and Bar{\i}{\c{s}} {\"O}zcan and Furkan K{\i}ra{\c{c}}},
        year={2021},
        url={https://openreview.net/forum?id=RKAKTnLzb8q}
}