90 citations
- Honda Research Institute, USAUS9 papers
- Carnegie Mellon UniversityUS6 papers
- University of California, BerkeleyUS6 papers
- Boston UniversityUS4 papers
- Duke UniversityUS3 papers
- Honda (Germany)DE3 papers
- Honda (Japan)JP3 papers
- Brown UniversityUS2 papers
- Cornell UniversityUS2 papers
- Massachusetts Institute of TechnologyUS2 papers
- Purdue University West LafayetteUS2 papers
- University of DelawareUS2 papers
8 papers · 1 filter
Occlusion-Aware Temporally Consistent Amodal Completion for 3D Human-Object Interaction Reconstruction
Hyungjun Doh, Dong In Lee, Seunggeun Chi +4
We introduce a novel framework for reconstructing dynamic human-object interactions from monocular video that overcomes challenges associated with occlusions and temporal inconsist…
RAIN: Reinforced Hybrid Attention Inference Network for Motion Forecasting
Jiachen Li, Fan Yang, Hengbo Ma +3
Motion forecasting plays a significant role in various domains (e.g., autonomous driving, human-robot interaction), which aims to predict future motion sequences given a set of his…
Uncertainty-aware Self-supervised 3D Data Association
Jianren Wang, Siddharth Ancha, Yi-Ting Chen +1
3D object trackers usually require training on large amounts of annotated data that is expensive and time-consuming to collect. Instead, we propose leveraging vast unlabeled datase…
Recognition and 3D Localization of Pedestrian Actions from Monocular Video
Jun Hayakawa, Behzad Dariush
Understanding and predicting pedestrian behavior is an important and challenging area of research for realizing safe and effective navigation strategies in automated and advanced d…
Ego-motion and Surrounding Vehicle State Estimation Using a Monocular Camera
Jun Hayakawa, Behzad Dariush
Understanding ego-motion and surrounding vehicle state is essential to enable automated driving and advanced driving assistance technologies. Typical approaches to solve this probl…
Goal-oriented Object Importance Estimation in On-road Driving Videos
Mingfei Gao, Ashish Tawari, Sujitha Martin
We formulate a new problem as Object Importance Estimation (OIE) in on-road driving videos, where the road users are considered as important objects if they have influence on the c…