Based on the encoder–decoder architecture, attribute-guided facial image completion can be achieved by decoding the latent representation from the encoder and the target attributes from the users.
Jun 7, 2020
Attributes guided facial image completion - ScienceDirect
www.sciencedirect.com › article › abs › pii
Jun 7, 2020 · We propose a novel deep learning approach to facial image completion with multiple controllable attributes (eg, gender and smiling).
Jan 19, 2023 · We propose an alternative user-guided inpainting architecture that manipulates facial attributes using a single reference image as the guide.
These methods try to reproduce the pixels in the missing regions of a facial image so that the completion results are indistinguishable from the original one.
Image inpainting is a technique of completing missing pixels such as occluded region restoration, distracting objects removal, and facial completion. Among ...
Jun 1, 2020 · Semantic Scholar extracted view of "Attributes guided facial image completion" by Jingtao Guo et al.
Oct 17, 2021 · In this work, we propose a novel attributes-guided face completion network (AttrFaceNet), which comprises a facial attribute prediction subnet ...
RGINP: Reference Guided Image Inpainting using Facial Attributes. This repository is a official Pytorch implementation of RGINP.
Missing: completion. | Show results with:completion.
This paper introduces a new face image re- trieval framework, where the input face query is augmented by both an adjustment vector that specifies the desired ...
Facial inpainting (or face completion) is the task of generating plausible facial structures for missing pixels in a face image.