35 citations · 65 across the 11 of their papers we have counts for
11 papers
ForecastOcc: Vision-based Semantic Occupancy Forecasting
Riya Mohan, Juana Valeria Hurtado, Rohit Mohan +1
Autonomous driving requires forecasting both geometry and semantics over time to effectively reason about future environment states. Existing vision-based occupancy forecasting met…
Hyperspectral Adapter for Semantic Segmentation with Vision Foundation Models
Juana Valeria Hurtado, Rohit Mohan, Abhinav Valada
Hyperspectral imaging (HSI) captures spatial information along with dense spectral measurements across numerous narrow wavelength bands. This rich spectral content has the potentia…
Learning Appearance and Motion Cues for Panoptic Tracking
Juana Valeria Hurtado, Sajad Marvi, Rohit Mohan +1
Panoptic tracking enables pixel-level scene interpretation of videos by integrating instance tracking in panoptic segmentation. This provides robots with a spatio-temporal understa…
Panoptic-Depth Forecasting
Juana Valeria Hurtado, Riya Mohan, Abhinav Valada
Forecasting the semantics and 3D structure of scenes is essential for robots to navigate and plan actions safely. Recent methods have explored semantic and panoptic scene forecasti…
Semantic Scene Segmentation for Robotics
Juana Valeria Hurtado, Abhinav Valada
Comprehensive scene understanding is a critical enabler of robot autonomy. Semantic segmentation is one of the key scene understanding tasks which is pivotal for several robotics a…
Panoptic Out-of-Distribution Segmentation
Rohit Mohan, Kiran Kumaraswamy, Juana Valeria Hurtado +2
Deep learning has led to remarkable strides in scene understanding with panoptic segmentation emerging as a key holistic scene interpretation task. However, the performance of pano…
Fairness and Bias in Robot Learning
Laura Londoño, Juana Valeria Hurtado, Nora Hertz +3
Machine learning has significantly enhanced the abilities of robots, enabling them to perform a wide range of tasks in human environments and adapt to our uncertain real world. Rec…
Feminist Perspective on Robot Learning Processes
Juana Valeria Hurtado, Valentina Mejia
As different research works report and daily life experiences confirm, learning models can result in biased outcomes. The biased learned models usually replicate historical discrim…
From Learning to Relearning: A Framework for Diminishing Bias in Social Robot Navigation
Juana Valeria Hurtado, Laura Londoño, Abhinav Valada
The exponentially increasing advances in robotics and machine learning are facilitating the transition of robots from being confined to controlled industrial spaces to performing n…
There is More than Meets the Eye: Self-Supervised Multi-Object Detection and Tracking with Sound by Distilling Multimodal Knowledge
Francisco Rivera Valverde, Juana Valeria Hurtado, Abhinav Valada
Attributes of sound inherent to objects can provide valuable cues to learn rich representations for object detection and tracking. Furthermore, the co-occurrence of audiovisual eve…
MOPT: Multi-Object Panoptic Tracking
Juana Valeria Hurtado, Rohit Mohan, Wolfram Burgard +1
Comprehensive understanding of dynamic scenes is a critical prerequisite for intelligent robots to autonomously operate in their environment. Research in this domain, which encompa…