From the 1 of 47 linked papers with an AI index.
1.4k citations · 2.8k across the 38 of their papers we have counts for
47 papers
Towards Motion Forecasting with Real-World Perception Inputs: Are End-to-End Approaches Competitive?
Yihong Xu, Loïck Chambon, Éloi Zablocki +4
Motion forecasting is crucial in enabling autonomous vehicles to anticipate the future trajectories of surrounding agents. To do so, it requires solving mapping, detection, trackin…
Diverse Probabilistic Trajectory Forecasting with Admissibility Constraints
Laura Calem, Hedi Ben-Younes, Patrick Pérez +1
Predicting multiple trajectories for road users is important for automated driving systems: ego-vehicle motion planning indeed requires a clear view of the possible motions of the…
Teachers in concordance for pseudo-labeling of 3D sequential data
Awet Haileslassie Gebrehiwot, Patrik Vacek, David Hurych +3
Automatic pseudo-labeling is a powerful tool to tap into large amounts of sequential unlabeled data. It is specially appealing in safety-critical applications of autonomous driving…
Raising context awareness in motion forecasting
Hédi Ben-Younes, Éloi Zablocki, Mickaël Chen +2
Learning-based trajectory prediction models have encountered great success, with the promise of leveraging contextual information in addition to motion history. Yet, we find that s…
Cross-modal Learning for Domain Adaptation in 3D Semantic Segmentation
Maximilian Jaritz, Tuan-Hung Vu, Raoul de Charette +2
Domain adaptation is an important task to enable learning when labels are scarce. While most works focus only on the image modality, there are many important multi-modal datasets.…
Explainability of deep vision-based autonomous driving systems: Review and challenges
Éloi Zablocki, Hédi Ben-Younes, Patrick Pérez +1
This survey reviews explainability methods for vision-based self-driving systems trained with behavior cloning. The concept of explainability has several facets and the need for ex…