10 citations · 37 across the 17 of their papers we have counts for
7 papers · 1 filter
Cloth2Tex: A Customized Cloth Texture Generation Pipeline for 3D Virtual Try-On
Daiheng Gao, Xu Chen, Xindi Zhang +5
Fabricating and designing 3D garments has become extremely demanding with the increasing need for synthesizing realistic dressed persons for a variety of applications, e.g. 3D virt…
TO-Rawnet: Improving RawNet with TCN and Orthogonal Regularization for Fake Audio Detection
Chenglong Wang, Jiangyan Yi, Jianhua Tao +4
Current fake audio detection relies on hand-crafted features, which lose information during extraction. To overcome this, recent studies use direct feature extraction from raw audi…
Detection of Cross-Dataset Fake Audio Based on Prosodic and Pronunciation Features
Chenglong Wang, Jiangyan Yi, Jianhua Tao +3
Existing fake audio detection systems perform well in in-domain testing, but still face many challenges in out-of-domain testing. This is due to the mismatch between the training a…
Cross-domain Augmentation Networks for Click-Through Rate Prediction
Xu Chen, Zida Cheng, Shuai Xiao +2
Data sparsity is an important issue for click-through rate (CTR) prediction, particularly when user-item interactions is too sparse to learn a reliable model. Recently, many works…
AG3D: Learning to Generate 3D Avatars from 2D Image Collections
Zijian Dong, Xu Chen, Jinlong Yang +3
While progress in 2D generative models of human appearance has been rapid, many applications require 3D avatars that can be animated and rendered. Unfortunately, most existing meth…
Learning to Detect Slip through Tactile Estimation of the Contact Force Field and its Entropy
Xiaohai Hu, Aparajit Venkatesh, Yusen Wan +5
Detection of slip during object grasping and manipulation plays a vital role in object handling. Existing solutions primarily rely on visual information to devise a strategy for gr…
Vid2Avatar: 3D Avatar Reconstruction from Videos in the Wild via Self-supervised Scene Decomposition
Chen Guo, Tianjian Jiang, Xu Chen +2
We present Vid2Avatar, a method to learn human avatars from monocular in-the-wild videos. Reconstructing humans that move naturally from monocular in-the-wild videos is difficult.…