1 code implementation • 23 Mar 2022 • Qian Huang, Zhipeng Dong, Yuzuru Takashima, Timothy J. Schulz, David J. Brady
Coherent illumination reflected by a remote target may be secondarily scattered by intermediate objects or materials.
1 code implementation • 16 Nov 2021 • Xing Li, Qian Huang, Zhijian Wang, Zhenjie Hou, Tianjin Yang
The key to our approach is to divide the main modeling operations into frame-level units executed in parallel, which greatly improves the efficiency of modeling point cloud sequences. Moreover, we propose to flatten the point cloud sequence into a new point data type named hyperpoint sequence that preserves the complete spatial structure of each frame.
2 code implementations • 30 Jun 2021 • Abhay Singh, Qian Huang, Sijia Linda Huang, Omkar Bhalerao, Horace He, Ser-Nam Lim, Austin R. Benson
Here, we demonstrate how simply adding a set of edges, which we call a \emph{proposal set}, to the graph as a pre-processing step can improve the performance of several link prediction algorithms.
Ranked #1 on
Link Property Prediction
on ogbl-ddi
no code implementations • 19 Jan 2021 • Chang Li, Qian Huang, Xing Li, Qianhan Wu
We employ depth motion images (DMI) as the templates to generate the multi-scale static representation of actions.
7 code implementations • ICLR 2021 • Qian Huang, Horace He, Abhay Singh, Ser-Nam Lim, Austin R. Benson
Graph Neural Networks (GNNs) are the predominant technique for learning over graphs.
Ranked #14 on
Node Property Prediction
on ogbn-products
1 code implementation • NeurIPS 2020 • Qian Huang, Horace He, Abhay Singh, Yan Zhang, Ser-Nam Lim, Austin Benson
Incorporating relational reasoning into neural networks has greatly expanded their capabilities and scope.
no code implementations • 13 Jan 2020 • Shanlin Sun, Yang Liu, Narisu Bai, Hao Tang, Xuming Chen, Qian Huang, Yong liu, Xiaohui Xie
Organs-at-risk (OAR) delineation in computed tomography (CT) is an important step in Radiation Therapy (RT) planning.
1 code implementation • ICCV 2019 • Qian Huang, Isay Katsman, Horace He, Zeqi Gu, Serge Belongie, Ser-Nam Lim
We show that we can select a layer of the source model to perturb without any knowledge of the target models while achieving high transferability.
no code implementations • 20 Nov 2018 • Qian Huang, Zeqi Gu, Isay Katsman, Horace He, Pian Pawakapan, Zhiqiu Lin, Serge Belongie, Ser-Nam Lim
Neural networks are vulnerable to adversarial examples, malicious inputs crafted to fool trained models.
no code implementations • CVPR 2018 • Qian Huang, Weixin Zhu, Yang Zhao, Linsen Chen, Yao Wang, Tao Yue, Xun Cao
In this paper, a new Multispectral Image Intrinsic Decomposition model (MIID) is presented to decompose the shading and reflectance from a single multispectral image.
no code implementations • 24 Feb 2018 • Qian Huang, Weixin Zhu, Yang Zhao, Linsen Chen, Yao Wang, Tao Yue, Xun Cao
In this paper, a Low Rank Multispectral Image Intrinsic Decomposition model (LRIID) is presented to decompose the shading and reflectance from a single multispectral image.