no code implementations • 24 Apr 2023 • Wanglong Lu, Xianta Jiang, Xiaogang Jin, Yong-Liang Yang, Minglun Gong, Tao Wang, Kaijie Shi, Hanli Zhao
Image inpainting is the task of filling in missing or masked region of an image with semantically meaningful contents.
no code implementations • 25 Mar 2023 • Yiqian Wu, Jing Zhang, Hongbo Fu, Xiaogang Jin
To better validate our pose-conditional 3D-aware generators, we develop a new FID measure to evaluate the 3D-level performance.
no code implementations • 5 May 2022 • Xiangjun Tang, He Wang, Bo Hu, Xu Gong, Ruifan Yi, Qilong Kou, Xiaogang Jin
Then, during generation, we design a transition model which is essentially a sampling strategy to sample from the learned manifold, based on the target frame and the aimed transition duration.
no code implementations • 5 May 2022 • Xiangjun Tang, Wenxin Sun, Yong-Liang Yang, Xiaogang Jin
In the second stage, we first reshape the reconstructed 3D face using a parametric reshaping model reflecting the weight change of the face, and then utilize the reshaped 3D face to guide the warping of video frames.
1 code implementation • 3 May 2022 • Xiaoyu Pan, Jiaming Mai, Xinwei Jiang, Dongxue Tang, Jingxiang Li, Tianjia Shao, Kun Zhou, Xiaogang Jin, Dinesh Manocha
We present a learning algorithm that uses bone-driven motion networks to predict the deformation of loose-fitting garment meshes at interactive rates.
no code implementations • 13 Feb 2022 • Wanglong Lu, Hanli Zhao, Xianta Jiang, Xiaogang Jin, YongLiang Yang, Min Wang, Jiankai Lyu, Kaijie Shi
We introduce a novel attribute similarity metric to encourage networks to learn the style of facial attributes from the exemplar in a self-supervised way.
2 code implementations • CVPR 2022 • Yiqian Wu, Yong-Liang Yang, Xiaogang Jin
Removing hair from portrait images is challenging due to the complex occlusions between hair and face, as well as the lack of paired portrait data with/without hair.
no code implementations • 8 Jan 2021 • Nannan Wu, Qianwen Chao, Yanzhen Chen, Weiwei Xu, Chen Liu, Dinesh Manocha, Wenxin Sun, Yi Han, Xinran Yao, Xiaogang Jin
Given a query shape and pose of the virtual agent, we synthesize the resulting clothing deformation by blending the Taylor expansion results of nearby anchoring points.
1 code implementation • 14 Nov 2019 • Bo Wang, Quan Chen, Min Zhou, Zhiqiang Zhang, Xiaogang Jin, Kun Gai
Feature matters for salient object detection.
no code implementations • 19 May 2017 • Xingping Dong, Jianbing Shen, Dongming Wu, Kan Guo, Xiaogang Jin, Fatih Porikli
In this paper, we propose a new quadruplet deep network to examine the potential connections among the training instances, aiming to achieve a more powerful representation.