18 citations · 126 across the 28 of their papers we have counts for
9 papers · 1 filter
SafeShift: Safety-Informed Distribution Shifts for Robust Trajectory Prediction in Autonomous Driving
Benjamin Stoler, Ingrid Navarro, Meghdeep Jana +3
As autonomous driving technology matures, safety and robustness of its key components, including trajectory prediction, is vital. Though real-world datasets, such as Waymo Open Mot…
MOSAIC: Learning Unified Multi-Sensory Object Property Representations for Robot Learning via Interactive Perception
Gyan Tatiya, Jonathan Francis, Ho-Hsiang Wu +2
A holistic understanding of object properties across diverse sensory modalities (e.g., visual, audio, and haptic) is essential for tasks ranging from object categorization to compl…
Traffic-Domain Video Question Answering with Automatic Captioning
Ehsan Qasemi, Jonathan M. Francis, Alessandro Oltramari
Video Question Answering (VidQA) exhibits remarkable potential in facilitating advanced machine reasoning capabilities within the domains of Intelligent Traffic Monitoring and Inte…
A Study of Situational Reasoning for Traffic Understanding
Jiarui Zhang, Filip Ilievski, Kaixin Ma +3
Intelligent Traffic Monitoring (ITMo) technologies hold the potential for improving road safety/security and for enabling smart city infrastructure. Understanding traffic situation…
What Went Wrong? Closing the Sim-to-Real Gap via Differentiable Causal Discovery
Peide Huang, Xilun Zhang, Ziang Cao +6
Training control policies in simulation is more appealing than on real robots directly, as it allows for exploring diverse states in an efficient manner. Yet, robot simulators inev…
Knowledge-enhanced Agents for Interactive Text Games
Prateek Chhikara, Jiarui Zhang, Filip Ilievski +2
Communication via natural language is a key aspect of machine intelligence, and it requires computational models to learn and reason about world concepts, with varying levels of su…
Regularizing Self-training for Unsupervised Domain Adaptation via Structural Constraints
Rajshekhar Das, Jonathan Francis, Sanket Vaibhav Mehta +3
Self-training based on pseudo-labels has emerged as a dominant approach for addressing conditional distribution shifts in unsupervised domain adaptation (UDA) for semantic segmenta…
Core Challenges in Embodied Vision-Language Planning
Jonathan Francis, Nariaki Kitamura, Felix Labelle +3
Recent advances in the areas of Multimodal Machine Learning and Artificial Intelligence (AI) have led to the development of challenging tasks at the intersection of Computer Vision…
Cross-Tool and Cross-Behavior Perceptual Knowledge Transfer for Grounded Object Recognition
Gyan Tatiya, Jonathan Francis, Jivko Sinapov
Humans learn about objects via interaction and using multiple perceptions, such as vision, sound, and touch. While vision can provide information about an object's appearance, non-…