no code implementations • 12 Feb 2024 • Shivanand Venkanna Sheshappanavar, Tejas Anvekar, Shivanand Kundargi, Yufan Wang, Chandra Kambhamettu
Existing datasets on groceries are mainly 2D images.
1 code implementation • IEEE/CVF International Conference on Computer Vision Workshops (ICCVW) 2023 • Akash Kumbar, Tejas Anvekar, Ramesh Ashok Tabib, Uma Mudenagudi
Our proposed implicit occupancy representation enables efficient point classification, effectively discerning points belonging to the surface from non-surface points.
1 code implementation • Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops 2023 • Akash Kumbar, Tejas Anvekar, Tulasi Amitha Vikrama, Ramesh Ashok Tabib, Uma Mudenagudi
TP-NoDe mitigates the need for task-specific training of upsampling networks for a specific upsampling ratio by reusing a point cloud denoising framework.
no code implementations • 13 Apr 2023 • Shivanand Kundargi, Tejas Anvekar, Ramesh Ashok Tabib, Uma Mudenagudi
Point clouds offer comprehensive and precise data regarding the contour and configuration of objects.
1 code implementation • 12 Apr 2023 • Tejas Anvekar, Dena Bazazian
In the realm of 3D-computer vision applications, point cloud few-shot learning plays a critical role.
Computational Efficiency Few-Shot 3D Point Cloud Classification +3
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.