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Keynote 1: Learning Vehicle Control without Explicit Supervision
Keynote 1: Learning Vehicle Control without Explicit Supervision
Prof. Dr. Daniel Cremers (given by Qadeer Khan)
Computer Vision & Artificial Intelligence
Technical University of Munich (TUM)
Keynote 2: Co-Training for Unsupervised Domain Adaptation of Semantic Segmentation Models
Keynote 2: Co-Training for Unsupervised Domain Adaptation of Semantic Segmentation Models
Prof. Antonio M. López
Computer Vision Center (CVC)
Universitat Autònoma de Barcelona (UAB)
Keynote 3: Understanding the Challenges When 3D Semantic Segmentation Faces Class Imbalanced and OOD Data
Keynote 3: Understanding the Challenges When 3D Semantic Segmentation Faces Class Imbalanced and OOD Data
Prof. Huijing Zhao
Department of Machine Intelligence
Peking University (PKU)
Keynote 4: Learning from Synthetic Data Generated by CARLA Simulator
Keynote 4: Learning from Synthetic Data Generated by CARLA Simulator
Prof. Luis M. Bergasa
Department of Electronics
University of Alcalá (UAH)
Keynote 5: From Scene Understanding to SLAM: Scalable Perception for Automated Driving
Keynote 5: From Scene Understanding to SLAM: Scalable Perception for Automated Driving
Prof. Abhinav Valada
Robot Learning Lab
University of Freiburg
Keynote 6: Event-based Fusion for Motion Deblurring with Cross-modal Attention
Keynote 6: Event-based Fusion for Motion Deblurring with Cross-modal Attention
Prof. Kaiwei Wang (given by Lei Sun)
State Key Laboratory of Modern Optical Instrumentation
Zhejiang University (ZJU)
Keynote 7: An Overview of Transfer Learning: A Practical View
Keynote 7: An Overview of Transfer Learning: A Practical View
Fernando German Torales Chorne
Bearcover GmbH
Keynote 8: Domain Adaptation and Label-Efficient Learning for Autonomous Driving
Keynote 8: Domain Adaptation and Label-Efficient Learning for Autonomous Driving
Dr. Dengxin Dai
Vision for Autonomous Systems (VAS) Group
Max Planck Institute for Informatics (MPII)
Keynote 9: Data Augmentation and Unsupervised Domain Adaptation Methods for Intelligent Vehicles
Keynote 9: Data Augmentation and Unsupervised Domain Adaptation Methods for Intelligent Vehicles
Dr. Yeqiang Qian
CyberC3 Intelligent Vehicle Lab
Shanghai Jiao Tong University (SJTU)
Keynote 10: Self-supervised 3D Perception for Autonomous Driving
Keynote 10: Self-supervised 3D Perception for Autonomous Driving
Prof. David Held
Robotics Institute and the director of the RPAD lab
Carnegie Mellon University (CMU)
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