no code implementations • 19 Jul 2023 • Vinicius Mariano Goncalves, Prashanth Krishnamurthy, Anthony Tzes, Farshad Khorrami
Control Barrier Functions and Quadratic Programming are increasingly used for designing controllers that consider critical safety constraints.
no code implementations • 12 Dec 2022 • Daitao Xing, Jinglin Shen, Chiuman Ho, Anthony Tzes
The exploration of mutual-benefit cross-domains has shown great potential toward accurate self-supervised depth estimation.
no code implementations • 24 Nov 2022 • Benjamin Kiefer, Matej Kristan, Janez Perš, Lojze Žust, Fabio Poiesi, Fabio Augusto de Alcantara Andrade, Alexandre Bernardino, Matthew Dawkins, Jenni Raitoharju, Yitong Quan, Adem Atmaca, Timon Höfer, Qiming Zhang, Yufei Xu, Jing Zhang, DaCheng Tao, Lars Sommer, Raphael Spraul, Hangyue Zhao, Hongpu Zhang, Yanyun Zhao, Jan Lukas Augustin, Eui-ik Jeon, Impyeong Lee, Luca Zedda, Andrea Loddo, Cecilia Di Ruberto, Sagar Verma, Siddharth Gupta, Shishir Muralidhara, Niharika Hegde, Daitao Xing, Nikolaos Evangeliou, Anthony Tzes, Vojtěch Bartl, Jakub Špaňhel, Adam Herout, Neelanjan Bhowmik, Toby P. Breckon, Shivanand Kundargi, Tejas Anvekar, Chaitra Desai, Ramesh Ashok Tabib, Uma Mudengudi, Arpita Vats, Yang song, Delong Liu, Yonglin Li, Shuman Li, Chenhao Tan, Long Lan, Vladimir Somers, Christophe De Vleeschouwer, Alexandre Alahi, Hsiang-Wei Huang, Cheng-Yen Yang, Jenq-Neng Hwang, Pyong-Kun Kim, Kwangju Kim, Kyoungoh Lee, Shuai Jiang, Haiwen Li, Zheng Ziqiang, Tuan-Anh Vu, Hai Nguyen-Truong, Sai-Kit Yeung, Zhuang Jia, Sophia Yang, Chih-Chung Hsu, Xiu-Yu Hou, Yu-An Jhang, Simon Yang, Mau-Tsuen Yang
The 1$^{\text{st}}$ Workshop on Maritime Computer Vision (MaCVi) 2023 focused on maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicle (USV), and organized several subchallenges in this domain: (i) UAV-based Maritime Object Detection, (ii) UAV-based Maritime Object Tracking, (iii) USV-based Maritime Obstacle Segmentation and (iv) USV-based Maritime Obstacle Detection.
no code implementations • 23 Mar 2022 • Omar Alfarisi, Zeyar Aung, Qingfeng Huang, Ashraf Al-Khateeb, Hamed Alhashmi, Mohamed Abdelsalam, Salem Alzaabi, Haifa Alyazeedi, Anthony Tzes
Planetary exploration depends heavily on 3D image data to characterize the static and dynamic properties of the rock and environment.
1 code implementation • 17 Oct 2021 • Daitao Xing, Nikolaos Evangeliou, Athanasios Tsoukalas, Anthony Tzes
Specifically, we exploit the inherent feature pyramid of a lightweight network (ShuffleNetV2) and reinforce it with a Transformer to construct a robust target-specific appearance model.
no code implementations • 24 Jun 2020 • Shuaihang Yuan, Xiang Li, Anthony Tzes, Yi Fang
To approach this problem, we propose a self-supervised approach that leverages the power of the deep neural network to learn a continuous flow function of 3D point clouds that can predict temporally consistent future motions and naturally bring out the correspondences among consecutive point clouds at the same time.