[visionlist] Call for attendence : 3D-DLAD-v4 Fourth workshop on 3D Deep Learning for Autonomous Driving at Intelligent Vehicules 2022

Ravi Kiran beedotkiran at gmail.com
Tue May 3 13:48:08 -05 2022


We invite potential attendees to the *3D-DLAD-v4* (Fourth 3D Deep Learning
for Autonomous Driving) workshop, the 7th workshop organized as part of the
DLAD workshop series.
It is organized as a part of the flagship automotive conference Intelligent
Vehicles https://iv2022.com/

Workshop Website : https://sites.google.com/view/3d-dlad-v4-iv2022/schedule
Workshop Type : Virtual Online
Registration : https://iv2022.com/registration
Location : Aachen, Germany
Date : 5 June 2022

*Contact*:
valada at cs.uni-freiburg.de
rvarun7777 at gmail.com
ravi.kiran at navya.tech
syogaman at qualcomm.com


*Key Topics in this workshop session : *3D deep learning on pointclouds,
Sensor calibration and fusion for autonomous driving,
Embedded deep learning for point-clouds,
Deep representations for Camera-Lidar Fusion.
Neural Radiance Fields (NERFS)
Large scale semantic segmentation

*3D-DLAD-v4 Workshop Speakers/Talks*
- Implicit Neural Representations for Novel View Appearance, Content and
Semantic Synthesis, Yiyi Liao, Professor, Zhejiang University (
https://yiyiliao.github.io/)
- Closed and Open Problems in 3D Perception for Self-Driving, Jonah
Philion, PhD student, University of Toronto (
https://www.cs.toronto.edu/~jphilion/)
- Next-Gen Sensor Fusion for Next-Gen Sensors and Driving Functions, Eric
Richter, Director Technology/Co-founder, BASELABS (https://www.baselabs.de/)
- Strategies and methods for automotive sensor fusion, Robert Laganiere,
Professor University of Ottawa, CEO Sensor Cortek (
https://www.site.uottawa.ca/~laganier/)
- Collaborative and Adversarial 3D Perception for Autonomous Driving,
Yiming Li, PhD Student, New York University (
https://roboticsyimingli.github.io/)
- Supervised and Unsupervised Approaches for LiDAR-Based Perception of
Autonomous Vehicles in Urban Environments, Prof. Dr. Cyrill Stachniss, Head
of Photogrammetry and Robotics Labs, University of Bonn (
https://www.ipb.uni-bonn.de/people/cyrill-stachniss/)
- 3D object detection survey and trends based on LiDAR, Steve Han, Deep
Learning Engineer at Qualcomm (https://www.linkedin.com/in/shizhonghan/)
- Multi-Sensor Safety Calibration for ADAS Applications, Mohammad Musa,
Founder & CEO at Deepen AI (https://www.deepen.ai/)
- Navya 3D Segmentation Dataset for large scale semantic segmentation,
Alexandre Almin, Navya (
https://www.linkedin.com/in/alexandre-almin-076aba105/)
- Exploiting Representational Sparsity to Improve 3D Object Detector
Runtime on Embedded Systems and Beyond, Kyle Vedder, PhD StudentComputer
Science, University of Pennsylvania (https://vedder.io/)
- DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection,
Yingwei Li, Ph.D. candidate in Computer Science at Johns Hopkins University
(https://yingwei.li/)
-  Leveraging Physics and Geometry in 3D Visual Perception, Dr. Christos
Sakaridis (https://people.ee.ethz.ch/~csakarid/)
- Few more talks TBA


*Accepted papers*- PVFusion: Point-Voxel Fusion for Multimodal 3D
Detection, Ke Wang*, zhichuang zhang, Tao Chen, Shulian Zhao
- Residual MBConv Submanifold Module for 3D LiDAR-based Object Detection,
Lie Guo*, Liang Huang, Zhao Yibing


*Workshop Organizers:*Abhinav Valada, University of Freiburg, Germany
Varun Ravi Kumar, Qualcomm
B Ravi Kiran, Navya, France
Senthil Yogamani, Qualcomm
Patrick Perez, Valeo.AI, France
Bharanidhar Duraisamy, Daimler, Germany
Xavier Savatier, Navya, France
Dan Levi, GM, Israel
Lars Kunze, Oxford University, UK
Markus Enzweiler, Daimler, Germany
Sumanth Chennupati, Wyze Labs, USA
Stefan Milz, Spleenlab.ai , Germany
Hazem Rashed, Valeo AI Research, Egypt
Jean-Emmanuel Deschaud, MINES ParisTech, France
Victor Vaquero, Research Engineer, IVEX.ai
Kuo-Chin Lien, Appen USA
Naveen Shankar Nagaraja, BMW Group, Munich
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://visionscience.com/pipermail/visionlist_visionscience.com/attachments/20220503/cf7ab9ab/attachment.html>


More information about the visionlist mailing list