Workshop
Machine Learning for Autonomous Driving
Xinshuo Weng · Jiachen Li · Nick Rhinehart · Daniel Omeiza · Ali Baheri · Rowan McAllister
Mon 13 Dec, 7:50 a.m. PST
We propose a full-day workshop, called “Machine Learning for Autonomous Driving” (ML4AD), as a venue for machine learning (ML) researchers to discuss research problems concerning autonomous driving (AD). Our goal is to promote ML research, and its real-world impact, on self-driving technologies. Full self-driving capability (“Level 5”) is far from solved and extremely complex, beyond the capability of any one institution or company, necessitating larger-scale communication and collaboration, which we believe workshop formats help provide.
We propose a large-attendance talk format of approximately 500 attendees, including (1) a call for papers with poster sessions and spotlight presentations; (2) keynote talks to communicate the state-of-the-art; (3) panel debates to discuss future research directions; (4) a call for challenge to encourage interaction around a common benchmark task; (5) social breaks for newer researchers to network and meet others.
Schedule
Mon 7:50 a.m. - 8:00 a.m.
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Opening Remarks
(
Opening Remarks
)
>
SlidesLive Video |
Xinshuo Weng 🔗 |
Mon 8:00 a.m. - 8:30 a.m.
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Reinforcement Learning for Autonomous Driving
(
Keynote Talk
)
>
SlidesLive Video |
Jeff Schneider · Jeff Schneider 🔗 |
Mon 8:30 a.m. - 8:40 a.m.
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Q&A: Jeff Schneider
(
Live Q/A
)
>
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🔗 |
Mon 8:40 a.m. - 9:10 a.m.
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AV2.0: Deploying End to End Deep Learning Policies at Fleet Scale
(
Keynote Talk
)
>
SlidesLive Video |
Alex Kendall 🔗 |
Mon 9:10 a.m. - 9:20 a.m.
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Q&A: Alex Kendall
(
Live Q/A
)
>
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🔗 |
Mon 9:20 a.m. - 9:30 a.m.
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(Best Paper) UMBRELLA: Uncertainty-Aware Model-Based Offline Reinforcement Learning Leveraging Planning
(
Oral
)
>
link
SlidesLive Video |
Christopher Diehl 🔗 |
Mon 9:30 a.m. - 10:30 a.m.
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Poster Session and Social ( Poster Session and Social ) > link | 🔗 |
Mon 10:30 a.m. - 11:00 a.m.
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Break
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🔗 |
Mon 11:00 a.m. - 11:30 a.m.
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Physics-Guided AI for Modeling Autonomous Vehicle Dynamics
(
Keynote Talk
)
>
SlidesLive Video |
Rose Yu · Rose Yu 🔗 |
Mon 11:30 a.m. - 11:40 a.m.
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Q&A: Rose Yu
(
Live Q/A
)
>
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🔗 |
Mon 11:40 a.m. - 12:10 p.m.
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The Ongoing Research in University of Michigan & Ford Center for Autonomous Vehicles (FCAV)
(
Keynote Talk
)
>
SlidesLive Video |
Matthew Johnson-Roberson 🔗 |
Mon 12:10 p.m. - 12:20 p.m.
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Q&A: Matthew Johnson-Roberson
(
Live Q/A
)
>
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🔗 |
Mon 12:20 p.m. - 1:20 p.m.
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CARLA Challenge
(
Challenge
)
>
link
SlidesLive Video |
German Ros 🔗 |
Mon 1:20 p.m. - 1:30 p.m.
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Break
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🔗 |
Mon 1:30 p.m. - 2:00 p.m.
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Fantastic Failures and Where to Find Them: Designing Safe, Robust Autonomy
(
Keynote Talk
)
>
SlidesLive Video |
Katherine Driggs-Campbell 🔗 |
Mon 2:00 p.m. - 2:10 p.m.
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Q&A: Katie Driggs-Campbell
(
Live Q/A
)
>
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🔗 |
Mon 2:10 p.m. - 2:40 p.m.
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Safely Learning Behaviors of Other Agents
(
Keynote Talk
)
>
SlidesLive Video |
Claire Tomlin 🔗 |
Mon 2:40 p.m. - 2:50 p.m.
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Q&A: Claire Tomlin
(
Live Q/A
)
>
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🔗 |
Mon 2:50 p.m. - 3:00 p.m.
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Spotlight Talks
(
Oral
)
>
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🔗 |
Mon 3:00 p.m. - 4:00 p.m.
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Poster Session and Social ( Poster Session and Social ) > link | 🔗 |
Mon 4:00 p.m. - 4:30 p.m.
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Learning Driving Agents from Simulation
(
Keynote Talk
)
>
SlidesLive Video |
Mark Palatucci 🔗 |
Mon 4:30 p.m. - 4:40 p.m.
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Q&A: Mark Palatucci
(
Live Q/A
)
>
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🔗 |
Mon 4:40 p.m. - 5:10 p.m.
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Autonomous Vehicle Decision-Making Policy Fast Adaptation Using Meta Reinforcement Learning
(
Keynote Talk
)
>
SlidesLive Video |
Songan Zhang 🔗 |
Mon 5:10 p.m. - 5:20 p.m.
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Q&A: Songan Zhang
(
Live Q/A
)
>
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🔗 |
Mon 5:20 p.m. - 5:50 p.m.
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Robotics for an ML-Driven World
(
Keynote Talk
)
>
SlidesLive Video |
Sarah Tang 🔗 |
Mon 5:50 p.m. - 6:00 p.m.
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Q&A: Sarah Tang
(
Live Q/A
)
>
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🔗 |
Mon 6:00 p.m. - 6:20 p.m.
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Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks
(
Challenge
)
>
link
SlidesLive Video |
Andrey Malinin 🔗 |
Mon 6:20 p.m. - 6:30 p.m.
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Closing Remarks
(
Closing Remarks
)
>
SlidesLive Video |
Rowan McAllister 🔗 |
-
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AA3DNet: Attention Augmented Real Time 3D Object Detection
(
Poster
)
>
SlidesLive Video |
Abhinav Sagar 🔗 |
-
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UMBRELLA: Uncertainty-Aware Model-Based Offline Reinforcement Learning Leveraging Planning
(
Poster
)
>
SlidesLive Video |
Christopher Diehl 🔗 |
-
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Compressing Sensor Data for Remote Assistance of Autonomous Vehicles using Deep Generative Models
(
Poster
)
>
SlidesLive Video |
Daniel Bogdoll · Marius Zöllner 🔗 |
-
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Efficient Unknown Object Detection with Discrepancy Networks for Semantic Segmentation
(
Poster
)
>
SlidesLive Video |
Ryo Kamoi · Takumi Iida · Kaname Tomite 🔗 |
-
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Self-supervised Sun Glare Detection CNN for Self-aware Autonomous Driving
(
Poster
)
>
SlidesLive Video |
Yiqiang CHEN · Feng Liu 🔗 |
-
|
Meta Guided Metric Learner for Overcoming Class Confusion in Few-Shot Road Object Detection
(
Poster
)
>
SlidesLive Video |
Anay Majee · Anbumani Subramanian · Kshitij Agrawal 🔗 |
-
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Watch out for the risky actors: Assessing risk in dynamic environments for safe driving
(
Poster
)
>
SlidesLive Video |
Saurabh Jha · Yan Miao · Zbigniew Kalbarczyk · Ravishankar Iyer 🔗 |
-
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A Step Towards Efficient Evaluation of Complex Perception Tasks in Simulation
(
Poster
)
>
SlidesLive Video |
Jonathan Sadeghi · Blaine Rogers · Sina Samangooei · Puneet Dokania · John Redford 🔗 |
-
|
Temporal Transductive Inference for Few-Shot Video Object Segmentation
(
Poster
)
>
SlidesLive Video |
Mennatullah Siam · Richard Wildes 🔗 |
-
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Spatial-Temporal Gated Transformersfor Efficient Video Processing
(
Poster
)
>
SlidesLive Video |
Yawei Li · Babak Ehteshami Bejnordi · Bert Moons · Tijmen Blankevoort · Amirhossein Habibian · Radu Timofte · Luc V Gool 🔗 |
-
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How Far Can I Go ? : A Self-Supervised Approach for Deterministic Video Depth Forecasting
(
Poster
)
>
SlidesLive Video |
Sauradip Nag · Nisarg Shah · Raghavendra Ramachandra 🔗 |
-
|
A Scenario-Based Platform for Testing Autonomous Vehicle Behavior Prediction Models in Simulation
(
Poster
)
>
SlidesLive Video |
Francis Indaheng · Edward Kim · Kesav Viswanadha · Jay Shenoy · Jinkyu Kim · Daniel Fremont · Sanjit Seshia 🔗 |
-
|
TITRATED: Learned Human Driving Behavior without Infractions via Amortized Inference
(
Poster
)
>
SlidesLive Video |
Vasileios Lioutas · Adam Scibior · Frank Wood 🔗 |
-
|
PolyTrack: Tracking with Bounding Polygons
(
Poster
)
>
SlidesLive Video |
Gaspar Faure · Hughes Perreault · Guillaume-Alexandre Bilodeau · Nicolas Saunier 🔗 |
-
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DriverGym: Democratising Reinforcement Learning for Autonomous Driving
(
Poster
)
>
SlidesLive Video |
Parth Kothari · Christian Perone · Luca Bergamini · Alexandre Alahi · Peter Ondruska 🔗 |
-
|
Incorporating Voice Instructions in Model-Based Reinforcement Learning for Self-Driving Cars
(
Poster
)
>
SlidesLive Video |
Mingze Wang · Ziyang Zhang · Grace Yang 🔗 |
-
|
Switching Recurrent Kalman Networks
(
Poster
)
>
SlidesLive Video |
Giao Nguyen-Quynh · Philipp Becker · Chen Qiu · Gerhard Neumann 🔗 |
-
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Object-Level Targeted Selection via Deep Template Matching
(
Poster
)
>
SlidesLive Video |
Suraj Kothawade · Michele Fenzi · Elmar Haussmann · Jose M. Alvarez · Christoph Angerer 🔗 |
-
|
Self-Supervised Pretraining for Scene Change Detection
(
Poster
)
>
SlidesLive Video |
Vijaya Raghavan Thiruvengadathan Ramkumar · Prashant Bhat · Elahe Arani · Bahram Zonooz 🔗 |
-
|
Does Thermal data make the detection systems more reliable?
(
Poster
)
>
SlidesLive Video |
Shruthi Gowda · Bahram Zonooz · Elahe Arani 🔗 |
-
|
Reinforcement Learning as an Alternative to Reachability Analysis for Falsification of AD Functions
(
Poster
)
>
SlidesLive Video |
Angel Molina Acosta · Alexander Schliep 🔗 |
-
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ORDER: Open World Object Detection on Road Scenes
(
Poster
)
>
SlidesLive Video |
Deepak Singh · Shyam Nandan Rai · Joseph K J · Rohit Saluja · Vineeth N Balasubramanian · Chetan Arora · Anbumani Subramanian · C.V. Jawahar 🔗 |
-
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Scalable Primitives for Generalized Sensor Fusion in Autonomous Vehicles
(
Poster
)
>
SlidesLive Video |
Sammy Sidhu · Aayush Ahuja 🔗 |
-
|
Hierarchical Adaptable and Transferable Networks (HATN) for Driving Behavior Prediction
(
Poster
)
>
SlidesLive Video |
Letian Wang · Yeping Hu · Liting Sun · Wei Zhan · Masayoshi TOMIZUKA · Changliu Liu 🔗 |
-
|
NSS-VAEs: Generative Scene Decomposition for Visual Navigable Space Construction
(
Poster
)
>
SlidesLive Video |
Zheng Chen · Lantao Liu 🔗 |
-
|
PKCAM: Previous Knowledge Channel Attention Module
(
Poster
)
>
SlidesLive Video |
Eslam MOHAMED-ABDELRAHMAN · Ahmad El Sallab · Mohsen Rashwan 🔗 |
-
|
MTL-TransMODS: Cascaded Multi-Task Learning for Moving Object Detection and Segmentation with Unified Transformers
(
Poster
)
>
SlidesLive Video |
Eslam MOHAMED-ABDELRAHMAN · Ahmad El Sallab 🔗 |
-
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Real-time Generalized Sensor Fusion with Transformers
(
Poster
)
>
SlidesLive Video |
Aayush Ahuja 🔗 |
-
|
Offline Reinforcement Learning for Autonomous Driving with Safety and Exploration Enhancement
(
Poster
)
>
SlidesLive Video |
TIANYU SHI · Dong Chen 🔗 |
-
|
Circular-Symmetric Correlation Layer
(
Poster
)
>
SlidesLive Video |
Bahare Azari · Deniz Erdogmus 🔗 |
-
|
Improved Object Detection in Thermal Imaging Through Context Enhancement and Information Fusion: A Case Study in Autonomous Driving
(
Poster
)
>
SlidesLive Video |
Junchi Bin · Ran Zhang · Shan Du · Erik Blasch · Zheng Liu 🔗 |
-
|
Monocular 3D Object Detection by Leveraging Self-Supervised Visual Pre-training
(
Poster
)
>
SlidesLive Video |
Can Erhan · Anıl Öztürk · Burak Gunel · Nazim Kemal Ure 🔗 |
-
|
Fast Polar Attentive 3D Object Detection based on Point Cloud
(
Poster
)
>
SlidesLive Video |
Manoj Bhat 🔗 |
-
|
Are Socially-Aware Trajectory Prediction Models Really Socially-Aware? ( Poster ) > link | Saeed Saadatnejad · Mohammadhossein Bahari 🔗 |