activity
20242026
collaborators

6 papers

cs.CV2026

Comparative Assessment of Deep Learning Architectures for Underwater Subsurface Kelp Forest Segmentation with The Kelp-o-Tron

Sundarabalan Balasubramanian, César Borja, Ana C. Murillo +5

Submerged kelp forests are vital coastal ecosystems that support marine biodiversity and ecosystem dynamics, yet accurate underwater kelp segmentation remains challenging due to op…

cs.CV2026

Leveraging existing sparse point annotations for benthic imagery dense segmentation

Cesar Borja, Breck A. McCollum, Jarret E. Byrnes +2

The health of marine ecosystems is a critical indicator of global environmental change, yet the physical constraints of underwater observation and the intrinsic challenges of proce…

cs.CV2025

SSeg: Active Sparse Point-Label Augmentation for Semantic Segmentation

Cesar Borja, Carlos Plou, Ruben Martinez-Cantin +1

Semantic segmentation is essential for automating remote sensing analysis in fields like ecology. However, fine-grained analysis of complex aerial or underwater imagery remains an…

cs.CV2025

FALCONEye: Finding Answers and Localizing Content in ONE-hour-long videos with multi-modal LLMs

Carlos Plou, Cesar Borja, Ruben Martinez-Cantin +1

Finding information in hour-long videos is a challenging task even for top-performing Vision Language Models (VLMs), as encoding visual content quickly exceeds available context wi…

cs.RO2024

Active Exploration in Bayesian Model-based Reinforcement Learning for Robot Manipulation

Carlos Plou, Ana C. Murillo, Ruben Martinez-Cantin

Efficiently tackling multiple tasks within complex environments, such as those found in robot manipulation, remains an ongoing challenge in robotics and an opportunity for data-dri…

cs.CV2024

EventSleep: Sleep Activity Recognition with Event Cameras

Carlos Plou, Nerea Gallego, Alberto Sabater +5

Event cameras are a promising technology for activity recognition in dark environments due to their unique properties. However, real event camera datasets under low-lighting condit…