1 code implementation • 3 Oct 2022 • Yahui Liu, Enver Sangineto, Yajing Chen, Linchao Bao, Haoxian Zhang, Nicu Sebe, Bruno Lepri, Marco De Nadai
Multi-domain image-to-image (I2I) translations can transform a source image according to the style of a target domain.
1 code implementation • 26 Sep 2021 • Yahui Liu, Yajing Chen, Linchao Bao, Nicu Sebe, Bruno Lepri, Marco De Nadai
The ISF manipulates the semantics of an input latent code to make the image generated from it lying in the desired visual domain.
no code implementations • 28 Jun 2021 • Yajing Chen, Zhenhua Jiao, Chenfeng Zhang, Luosai Zhang
This paper studies the housing market problem introduced by Shapley and Scarf (1974).
no code implementations • CVPR 2021 • Yahui Liu, Enver Sangineto, Yajing Chen, Linchao Bao, Haoxian Zhang, Nicu Sebe, Bruno Lepri, Wei Wang, Marco De Nadai
In this paper, we propose a new training protocol based on three specific losses which help a translation network to learn a smooth and disentangled latent style space in which: 1) Both intra- and inter-domain interpolations correspond to gradual changes in the generated images and 2) The content of the source image is better preserved during the translation.
no code implementations • 19 Apr 2021 • Yajing Chen, Patrick Harless, Zhenhua Jiao
Equal-rank envy-freeness implies equal treatment of equals.
no code implementations • 19 Apr 2021 • Siwei Chen, Yajing Chen, Chia-Ling Hsu
School choice is of great importance both in theory and practice.
2 code implementations • 12 Oct 2020 • Linchao Bao, Xiangkai Lin, Yajing Chen, Haoxian Zhang, Sheng Wang, Xuefei Zhe, Di Kang, HaoZhi Huang, Xinwei Jiang, Jue Wang, Dong Yu, Zhengyou Zhang
We present a fully automatic system that can produce high-fidelity, photo-realistic 3D digital human heads with a consumer RGB-D selfie camera.
1 code implementation • 25 Oct 2019 • Yajing Chen, Fanzi Wu, Zeyu Wang, Yibing Song, Yonggen Ling, Linchao Bao
The displacement map and the coarse model are used to render a final detailed face, which again can be compared with the original input image to serve as a photometric loss for the second stage.
1 code implementation • CVPR 2019 • Fanzi Wu, Linchao Bao, Yajing Chen, Yonggen Ling, Yibing Song, Songnan Li, King Ngi Ngan, Wei Liu
The main ingredient of the view alignment loss is a differentiable dense optical flow estimator that can backpropagate the alignment errors between an input view and a synthetic rendering from another input view, which is projected to the target view through the 3D shape to be inferred.
no code implementations • 13 Sep 2017 • Yajing Chen, Shikui Tu, Yuqi Yi, Lei Xu
Moreover, the combination of CNN encoder and removal of KL-divergence, i. e., the sketch-pix2seq model, had better performance in learning and generating sketches of multiple categories and showed promising results in creativity tasks.