no code implementations • 29 Jul 2024 • Zhixuan Chu, Hui Ding, Guang Zeng, Shiyu Wang, Yiming Li
Although the widespread use of AI systems in today's world is growing, many current AI systems are found vulnerable due to hidden bias and missing information, especially in the most commonly used forecasting system.
no code implementations • 8 Jul 2023 • Tong Xue, Haixia Zhang, Hui Ding, Dongfeng Yuan
The existing computation and communication (2C) optimization schemes for vehicular edge computing (VEC) networks mainly focus on the physical domain without considering the influence from the social domain.
no code implementations • 27 Jun 2023 • Haowei Li, Wenqing Yan, Du Liu, Long Qian, Yuxing Yang, Yihao Liu, Zhe Zhao, Hui Ding, Guangzhi Wang
The head surface is reconstructed using depth data for spatial registration, avoiding fixing tracking targets rigidly on the patient's skull.
1 code implementation • CVPR 2023 • Jiang Liu, Hui Ding, Zhaowei Cai, Yuting Zhang, Ravi Kumar Satzoda, Vijay Mahadevan, R. Manmatha
In this work, instead of directly predicting the pixel-level segmentation masks, the problem of referring image segmentation is formulated as sequential polygon generation, and the predicted polygons can be later converted into segmentation masks.
Ranked #1 on Referring Expression Segmentation on ReferIt (using extra training data)
no code implementations • 22 Aug 2022 • Zhixuan Chu, Hui Ding, Guang Zeng, Yuchen Huang, Tan Yan, Yulin kang, Sheng Li
In this paper, we provide an in-depth analysis of the underlying parse tree-like structure involved in the effect prediction task and we further establish a Hierarchical Capsule Prediction Network (HapNet) for predicting the effects of marketing campaigns.
1 code implementation • ICCV 2021 • Tianchen Zhao, Xiang Xu, Mingze Xu, Hui Ding, Yuanjun Xiong, Wei Xia
We propose a new method to detect deepfake images using the cue of the source feature inconsistency within the forged images.
no code implementations • 12 May 2020 • Hui Ding, Peng Zhou, Rama Chellappa
Recognizing the expressions of partially occluded faces is a challenging computer vision problem.
Facial Expression Recognition Facial Expression Recognition (FER)
no code implementations • 12 Sep 2017 • Hui Ding, Hao Zhou, Shaohua Kevin Zhou, Rama Chellappa
First, a weakly-supervised face region localization network is designed to automatically detect regions (or parts) specific to attributes.
2 code implementations • 12 Sep 2017 • Hui Ding, Kumar Sricharan, Rama Chellappa
To address these limitations, we propose an Expression Generative Adversarial Network (ExprGAN) for photo-realistic facial expression editing with controllable expression intensity.
no code implementations • 19 Aug 2017 • Kumar Sricharan, Raja Bala, Matthew Shreve, Hui Ding, Kumar Saketh, Jin Sun
We introduce a new model for building conditional generative models in a semi-supervised setting to conditionally generate data given attributes by adapting the GAN framework.
no code implementations • 21 Sep 2016 • Hui Ding, Shaohua Kevin Zhou, Rama Chellappa
In this paper, we present FaceNet2ExpNet, a novel idea to train an expression recognition network based on static images.
Ranked #1 on Facial Expression Recognition (FER) on CK+