<div dir="ltr"><div style="margin:0px;padding:0px;border:0px;font-variant-numeric:inherit;font-variant-east-asian:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:Calibri,Arial,Helvetica,sans-serif;vertical-align:baseline;color:rgb(0,0,0)"><span style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline;color:inherit">We apologize in advance for multiple reposts/copies.</span><br></div><div dir="ltr" style="margin:0px;padding:0px;border:0px;font-variant-numeric:inherit;font-variant-east-asian:inherit;font-stretch:inherit;font-size:14px;line-height:inherit;vertical-align:baseline;color:rgb(0,0,0)"><div style="margin:0px;padding:0px;border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:Calibri,Arial,Helvetica,sans-serif;vertical-align:baseline"><div style="margin:0px;padding:0px;border:0px;font-style:inherit;font-variant:inherit;font-weight:inherit;font-stretch:inherit;font-size:12pt;line-height:inherit;font-family:inherit;vertical-align:baseline"><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline"> </div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline"><b>CALL FOR PAPERS 3D-DLAD-v4 2022</b></div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline"><br></div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline"><b>3D-DLAD-v4 (Fourth 3D Deep Learning for Autonomous Driving) workshop<span style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline;color:inherit"> </span></b>is the 7th workshop organized as part of DLAD workshop series. It is organized as a part of the flagship automotive conference Intelligent Vehicles https://<span class="gmail-x_markzuegyigl7" style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline;color:inherit">iv</span><a href="http://2022.com/">2022.com/</a>.</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline"><br></div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Deep Learning has become a de-facto tool in Computer Vision and 3D processing with boosted performance and accuracy for diverse tasks such as object classification, detection, optical flow estimation, motion segmentation, mapping, etc. Lidar sensors are playing an important role in the development of Autonomous Vehicles as they overcome some of the many drawbacks of a camera-based system, such as degraded performance under changes in illumination and weather conditions. In addition, Lidar sensors capture a wider field of view, and directly obtain 3D information. This is essential to assure the security of the different agents and obstacles in the scene. It is a computationally challenging task to process more than 100k points per scan in realtime within modern perception pipelines. Following the said motivations, finally to address the growing interest in deep representation learning for lidar point-clouds, in both academic as well as industrial research domains for autonomous driving, we invite submissions to the current workshop to disseminate the latest research.</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline"><br></div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">We are soliciting contributions in deep learning on 3D data applied to autonomous driving in (but not limited to) the following topics. Please feel free to contact us if there are any questions. The workshop papers are reviewed under the same procedure as the conference papers, and they will also be published in the proceeding together with the conference papers.</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline"><br></div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline"><b>TOPICS</b><span style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline;color:inherit"> </span>:</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Deep Learning for Lidar based clustering, road extraction object detection and/or tracking.</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Deep Learning for Radar pointclouds</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Deep Learning for TOF sensor-based driver monitoring</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">New lidar based technologies and sensors.</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Deep Learning for Lidar localization, VSLAM, meshing, pointcloud inpainting</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Deep Learning for Odometry and Map/HDmaps generation with Lidar cues.</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Deep fusion of automotive sensors (Lidar, Camera, Radar).</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Design of datasets and active learning methods for pointclouds</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Synthetic Lidar sensors & Simulation-to-real transfer learning</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Cross-modal feature extraction for Sparse output sensors like Lidar.</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Generalization techniques for different Lidar sensors, multi-Lidar setup and point densities.</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Lidar based maps, HDmaps, prior maps, occupancy grids</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Real-time implementation on embedded platforms (Efficient design & hardware accelerators).</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Challenges of deployment in a commercial system (Functional safety & High accuracy).</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">End to end learning of driving with Lidar information (Single model & modular end-to-end)</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Deep learning for dense Lidar point cloud generation from sparse Lidars and other modalities</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline"><br></div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline"><b>Workshop link</b><span style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline;color:inherit"> </span>: <a href="https://sites.google.com/view/3d-dlad-v4-">https://sites.google.com/view/3d-dlad-v4-</a><span class="gmail-x_markzuegyigl7" style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline;color:inherit">iv</span>2022/home</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline"><b>Submission instructions</b><span style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline;color:inherit"> </span>: https://<span class="gmail-x_markzuegyigl7" style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline;color:inherit">iv</span><a href="http://2022.com/program/workshops">2022.com/program/workshops</a></div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline"><br></div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline"><b>Location</b><span style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline;color:inherit"> </span>: Aachen, Germany</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline"><b>Workshop papers submission deadline</b>: March 8th,<span style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline;color:inherit"> </span><span class="gmail-x_markf0of8p2cl" style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline;color:inherit">2022</span></div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline"><b>Acceptation/Rejection Notification</b>: April 22nd,<span style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline;color:inherit"> </span><span class="gmail-x_markf0of8p2cl" style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline;color:inherit">2022</span></div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline"><b>Final paper submission</b>: May 1st,<span style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline;color:inherit"> </span><span class="gmail-x_markf0of8p2cl" style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline;color:inherit">2022</span></div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline"><b>Contact</b>: <a href="mailto:valada@cs.uni-freiburg.de">valada@cs.uni-freiburg.de</a> <a href="mailto:rvarun7777@gmail.com">rvarun7777@gmail.com</a> ravi.kiran@navya.tech <a href="mailto:syogaman@qualcomm.com">syogaman@qualcomm.com</a></div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline"><br></div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline"><b>Workshop Organizers:</b></div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Abhinav Valada, University of Freiburg, Germany</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Varun Ravi Kumar, Qualcomm</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">B Ravi Kiran, Navya, France</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Senthil Yogamani, Qualcomm</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Patrick Perez, Valeo.AI, France</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Bharanidhar Duraisamy, Daimler, Germany<br></div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Dan Levi, GM, Israel</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Lars Kunze, Oxford University, UK</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Markus Enzweiler, Daimler, Germany</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline"><span style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Xavier Savatier, Navya</span><br></div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Sumanth Chennupati, Wyze Labs, USA</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Stefan Milz, Spleenlab.ai , Germany</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Hazem Rashed, Valeo AI Research, Egypt</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Jean-Emmanuel Deschaud, MINES ParisTech, France</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Victor Vaquero, Research Engineer,<span style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline;color:inherit"> </span><span class="gmail-x_markzuegyigl7" style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline;color:inherit">IV</span>EX.ai</div><div style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Kuo-Chin Lien, Appen USA</div><span style="margin:0px;padding:0px;border:0px;font:inherit;vertical-align:baseline">Naveen Shankar Nagaraja, BMW Group, Munich</span></div></div></div><div><br></div></div>