no code implementations • 25 Apr 2024 • Xiaohong Liu, Xiongkuo Min, Guangtao Zhai, Chunyi Li, Tengchuan Kou, Wei Sun, HaoNing Wu, Yixuan Gao, Yuqin Cao, ZiCheng Zhang, Xiele Wu, Radu Timofte, Fei Peng, Huiyuan Fu, Anlong Ming, Chuanming Wang, Huadong Ma, Shuai He, Zifei Dou, Shu Chen, Huacong Zhang, Haiyi Xie, Chengwei Wang, Baoying Chen, Jishen Zeng, Jianquan Yang, Weigang Wang, Xi Fang, Xiaoxin Lv, Jun Yan, Tianwu Zhi, Yabin Zhang, Yaohui Li, Yang Li, Jingwen Xu, Jianzhao Liu, Yiting Liao, Junlin Li, Zihao Yu, Yiting Lu, Xin Li, Hossein Motamednia, S. Farhad Hosseini-Benvidi, Fengbin Guan, Ahmad Mahmoudi-Aznaveh, Azadeh Mansouri, Ganzorig Gankhuyag, Kihwan Yoon, Yifang Xu, Haotian Fan, Fangyuan Kong, Shiling Zhao, Weifeng Dong, Haibing Yin, Li Zhu, Zhiling Wang, Bingchen Huang, Avinab Saha, Sandeep Mishra, Shashank Gupta, Rajesh Sureddi, Oindrila Saha, Luigi Celona, Simone Bianco, Paolo Napoletano, Raimondo Schettini, Junfeng Yang, Jing Fu, Wei zhang, Wenzhi Cao, Limei Liu, Han Peng, Weijun Yuan, Zhan Li, Yihang Cheng, Yifan Deng, Haohui Li, Bowen Qu, Yao Li, Shuqing Luo, Shunzhou Wang, Wei Gao, Zihao Lu, Marcos V. Conde, Xinrui Wang, Zhibo Chen, Ruling Liao, Yan Ye, Qiulin Wang, Bing Li, Zhaokun Zhou, Miao Geng, Rui Chen, Xin Tao, Xiaoyu Liang, Shangkun Sun, Xingyuan Ma, Jiaze Li, Mengduo Yang, Haoran Xu, Jie zhou, Shiding Zhu, Bohan Yu, Pengfei Chen, Xinrui Xu, Jiabin Shen, Zhichao Duan, Erfan Asadi, Jiahe Liu, Qi Yan, Youran Qu, Xiaohui Zeng, Lele Wang, Renjie Liao
A total of 196 participants have registered in the video track.
no code implementations • 20 Apr 2024 • Xi Fang, Weigang Wang, Xiaoxin Lv, Jun Yan
It is essential to build an effective quality assessment framework to provide a quantifiable evaluation of different images or videos based on the AIGC technologies.
no code implementations • 27 Feb 2024 • Xi Fang, Weijie Xu, Fiona Anting Tan, Jiani Zhang, Ziqing Hu, Yanjun Qi, Scott Nickleach, Diego Socolinsky, Srinivasan Sengamedu, Christos Faloutsos
Recent breakthroughs in large language modeling have facilitated rigorous exploration of their application in diverse tasks related to tabular data modeling, such as prediction, tabular data synthesis, question answering, and table understanding.
1 code implementation • 4 Feb 2024 • Liang Qiao, Jun Shi, Xiaoyu Hao, Xi Fang, Minfan Zhao, Ziqi Zhu, Junshi Chen, Hong An, Bing Li, Honghui Yuan, Xinyang Wang
Tensor program optimization on Deep Learning Accelerators (DLAs) is critical for efficient model deployment.
1 code implementation • 1 Feb 2024 • Weijie Xu, Zicheng Huang, Wenxiang Hu, Xi Fang, Rajesh Kumar Cherukuri, Naumaan Nayyar, Lorenzo Malandri, Srinivasan H. Sengamedu
The data generation pipeline is transferable and can be easily adapted for labeled conversation data generation in other domains.
no code implementations • 26 Oct 2023 • Shuai Yang, Zhifei Chen, Pengguang Chen, Xi Fang, Shu Liu, Yingcong Chen
Defect inspection is paramount within the closed-loop manufacturing system.
no code implementations • 20 Jul 2023 • Xi Fang, Daeseung Kim, Xuanang Xu, Tianshu Kuang, Nathan Lampen, Jungwook Lee, Hannah H. Deng, Jaime Gateno, Michael A. K. Liebschner, James J. Xia, Pingkun Yan
Our framework consists of a bony planner network that estimates the bony movements required to achieve the desired facial outcome and a facial simulator network that can simulate the possible facial changes resulting from the estimated bony movement plans.
no code implementations • 25 Oct 2022 • Huan Hua, Jun Yan, Xi Fang, Weiquan Huang, Huilin Yin, Wancheng Ge
With the utilization of such a framework, the influence of non-robust features could be mitigated to strengthen the adversarial robustness.
no code implementations • 4 Oct 2022 • Xi Fang, Daeseung Kim, Xuanang Xu, Tianshu Kuang, Hannah H. Deng, Joshua C. Barber, Nathan Lampen, Jaime Gateno, Michael A. K. Liebschner, James J. Xia, Pingkun Yan
In this work, we propose an Attentive Correspondence assisted Movement Transformation network (ACMT-Net) to estimate the facial appearance by transforming the bony movement to facial soft tissue through a point-to-point attentive correspondence matrix.
1 code implementation • 20 Jul 2020 • Hanqing Chao, Xi Fang, Jiajin Zhang, Fatemeh Homayounieh, Chiara D. Arru, Subba R. Digumarthy, Rosa Babaei, Hadi K. Mobin, Iman Mohseni, Luca Saba, Alessandro Carriero, Zeno Falaschi, Alessio Pasche, Ge Wang, Mannudeep K. Kalra, Pingkun Yan
Management of high-risk patients with early intervention is a key to lower the fatality rate of COVID-19 pneumonia, as a majority of patients recover naturally.
1 code implementation • 1 Jan 2020 • Xi Fang, Pingkun Yan
Shortage of fully annotated datasets has been a limiting factor in developing deep learning based image segmentation algorithms and the problem becomes more pronounced in multi-organ segmentation.
no code implementations • 24 Oct 2019 • Xi Fang, Bo Du, Sheng Xu, Bradford J. Wood, Pingkun Yan
Automatic medical image segmentation, an essential component of medical image analysis, plays an importantrole in computer-aided diagnosis.
no code implementations • 6 Mar 2018 • Xi Fang, Zengmao Wang, Xinyao Tang, Chen Wu
Simultaneously, our proposed method makes full use of the label information, and the proposed active learning is designed based on multiple classes.
1 code implementation • 3 Dec 2017 • Xingyu Chen, Junzhi Yu, Shihan Kong, Zhengxing Wu, Xi Fang, Li Wen
More specifically, an underwater index is investigated to describe underwater properties, and a loss function based on the underwater index is designed to train the critic branch for underwater noise suppression.