no code implementations • 19 Mar 2024 • Qi Li, Tzu-Chen Chiu, Hsiang-Wei Huang, Min-Te Sun, Wei-Shinn Ku
In this paper, we introduce the VideoBadminton dataset derived from high-quality badminton footage.
no code implementations • 7 Mar 2024 • Bohan Liu, Zijie Zhang, Peixiong He, Zhensen Wang, Yang Xiao, Ruimeng Ye, Yang Zhou, Wei-Shinn Ku, Bo Hui
The Lottery Ticket Hypothesis (LTH) states that a dense neural network model contains a highly sparse subnetwork (i. e., winning tickets) that can achieve even better performance than the original model when trained in isolation.
no code implementations • 10 May 2023 • Ai-Te Kuo, Haiquan Chen, Yu-Hsuan Kuo, Wei-Shinn Ku
Early detection of mental disorder is crucial as it enables prompt intervention and treatment, which can greatly improve outcomes for individuals suffering from debilitating mental affliction.
no code implementations • 3 May 2023 • Bo Hui, Da Yan, Xiaolong Ma, Wei-Shinn Ku
Therefore, we propose two techniques to improve GNN performance when the graph sparsity is high.
no code implementations • 15 Aug 2022 • Chia Hong Tseng, Jie Zhang, Min-Te Sun, Kazuya Sakai, Wei-Shinn Ku
To better utilize the lane information, the lanes which are in opposite direction to target agent are not likely to be taken by the target agent and are consequently filtered out.
1 code implementation • 2 Apr 2022 • Bo Hui, Wenlu Wang, Jiao Yu, Zhitao Gong, Wei-Shinn Ku, Min-Te Sun, Hua Lu
Based on the inference method and tracking models, we develop innovative indoor range and k nearest neighbor (kNN) query algorithms.
1 code implementation • 14 Oct 2021 • Jie Zhang, Bo Hui, Po-Wei Harn, Min-Te Sun, Wei-Shinn Ku
We test our model on several graph datasets including directed homogeneous and heterogeneous graphs.
no code implementations • 22 Dec 2020 • Tian Xia, Wei-Shinn Ku
To address the above challenges, we propose a new graph neural network architecture to represent the proteins as 3D graphs and predict both distance geometric graph representation and dihedral geometric graph representation together.
no code implementations • 28 Aug 2019 • Jingjing Li, Wenlu Wang, Wei-Shinn Ku, Yingtao Tian, Haixun Wang
A natural language interface (NLI) to databases is an interface that translates a natural language question to a structured query that is executable by database management systems (DBMS).
1 code implementation • CVPR 2019 • Michael A. Alcorn, Qi Li, Zhitao Gong, Chengfei Wang, Long Mai, Wei-Shinn Ku, Anh Nguyen
Using our framework and a self-assembled dataset of 3D objects, we investigate the vulnerability of DNNs to OoD poses of well-known objects in ImageNet.
2 code implementations • 7 Sep 2018 • Wenlu Wang, Yingtao Tian, Hongyu Xiong, Haixun Wang, Wei-Shinn Ku
In this work, we introduce a general purpose transfer-learnable NLI with the goal of learning one model that can be used as NLI for any relational database.
1 code implementation • 22 Jan 2018 • Zhitao Gong, Wenlu Wang, Bo Li, Dawn Song, Wei-Shinn Ku
In addition, we empirically show that WMD is closely related to the quality of adversarial texts.
1 code implementation • 17 Apr 2017 • Zhitao Gong, Wenlu Wang, Wei-Shinn Ku
Adversarial attack has cast a shadow on the massive success of deep neural networks.