Image Composition with Depth Registration
Zan Li, Wencheng Wang, Fei Hou
Abstract
Handling occlusions is still a challenging problem for image composition. It always requires the source contents to be completely in front of the target contents or needs manual interventions to adjust occlusions, which is very tedious. Though several methods have suggested exploiting priors or learning techniques for promoting occlusion determination, their potentials are much limited. This paper addresses the challenge by presenting a depth registration method for merging the source contents seamlessly into the 3D space that the target image represents. Thus, the occlusions between the source contents and target contents can be conveniently handled through pixel-wise depth comparisons, allowing the user to more efficiently focus on the designs for image composition. Experimental results show that we can conveniently handle occlusions in image composition and improve efficiency by about 4 times compared to Photoshop.
BibTeX
@inproceedings{ijcai2023p126,
title = {Image Composition with Depth Registration},
author = {Li, Zan and Wang, Wencheng and Hou, Fei},
booktitle = {Proceedings of the Thirty-Second International Joint Conference on
Artificial Intelligence, {IJCAI-23}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Edith Elkind},
pages = {1134--1141},
year = {2023},
month = {8},
note = {Main Track},
doi = {10.24963/ijcai.2023/126},
url = {https://doi.org/10.24963/ijcai.2023/126},
}