226 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Toyota Research Institute8 papers
- Massachusetts Institute of TechnologyUS5 papers
- Toyota Central Research and Development Laboratories (Japan)JP5 papers
- Keio UniversityJP4 papers
- University of California, BerkeleyUS4 papers
- University of MichiganUS3 papers
- Ann Arbor Center for Independent LivingUS2 papers
- Columbia UniversityUS2 papers
- Georgia State UniversityUS2 papers
- IBM Research - TokyoJP2 papers
- Infotech Soft (United States)US2 papers
- Institut national de recherche en sciences et technologies du numériqueFR2 papers
10 papers · 1 filter
The Way to my Heart is through Contrastive Learning: Remote Photoplethysmography from Unlabelled Video
John Gideon, Simon Stent
The ability to reliably estimate physiological signals from video is a powerful tool in low-cost, pre-clinical health monitoring. In this work we propose a new approach to remote p…
Ex-DoF: Expansion of Action Degree-of-Freedom with Virtual Camera Rotation for Omnidirectional Image
Kosuke Tahara, Noriaki Hirose
Inter-robot transfer of training data is a little explored topic in learning- and vision-based robot control. Here we propose a transfer method from a robot with a lower Degree-of-…
Seeking Similarities over Differences: Similarity-based Domain Alignment for Adaptive Object Detection
Farzaneh Rezaeianaran, Rakshith Shetty, Rahaf Aljundi +3
In order to robustly deploy object detectors across a wide range of scenarios, they should be adaptable to shifts in the input distribution without the need to constantly annotate…
Warp-Refine Propagation: Semi-Supervised Auto-labeling via Cycle-consistency
Aditya Ganeshan, Alexis Vallet, Yasunori Kudo +5
Deep learning models for semantic segmentation rely on expensive, large-scale, manually annotated datasets. Labelling is a tedious process that can take hours per image. Automatica…
Accuracy on the Line: On the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization
John Miller, Rohan Taori, Aditi Raghunathan +6
For machine learning systems to be reliable, we must understand their performance in unseen, out-of-distribution environments. In this paper, we empirically show that out-of-distri…
Euro-PVI: Pedestrian Vehicle Interactions in Dense Urban Centers
Apratim Bhattacharyya, Daniel Olmeda Reino, Mario Fritz +1
Accurate prediction of pedestrian and bicyclist paths is integral to the development of reliable autonomous vehicles in dense urban environments. The interactions between vehicle a…
MarioNette: Self-Supervised Sprite Learning
Dmitriy Smirnov, Michael Gharbi, Matthew Fisher +3
Artists and video game designers often construct 2D animations using libraries of sprites -- textured patches of objects and characters. We propose a deep learning approach that de…
The Logical Options Framework
Brandon Araki, Xiao Li, Kiran Vodrahalli +3
Learning composable policies for environments with complex rules and tasks is a challenging problem. We introduce a hierarchical reinforcement learning framework called the Logical…
Motion Estimation of Connected and Automated Vehicles under Communication Delay and Packet Loss of V2X Communications
Ziran Wang, Kyungtae Han, Prashant Han
The emergence of the connected and automated vehicle (CAV) technology enables numerous advanced applications in our transportation system, benefiting our daily travels in terms of…
Planning for Automated Vehicles with Human Trust
Shili Sheng, Erfan Pakdamanian, Kyungtae Han +4
Recent work has considered personalized route planning based on user profiles, but none of it accounts for human trust. We argue that human trust is an important factor to consider…