no code implementations • 16 Mar 2024 • Mariia Khan, Yue Qiu, Yuren Cong, Jumana Abu-Khalaf, David Suter, Bodo Rosenhahn
The foundational Segment Anything Model (SAM) is designed for promptable multi-class multi-instance segmentation but tends to output part or sub-part masks in the "everything" mode for various real-world applications.
no code implementations • 10 Sep 2023 • Muraleekrishna Gopinathan, Jumana Abu-Khalaf, David Suter, Sidike Paheding, Nathir A. Rawashdeh
We show that local-global planning based on locality knowledge and predicting the indoor layout allows the agent to efficiently select the appropriate action.
no code implementations • 4 Sep 2023 • Sharjeel Tahir, Syed Afaq Shah, Jumana Abu-Khalaf
From the last decade, researchers in the field of machine learning (ML) and assistive developmental robotics (ADR) have taken an interest in artificial empathy (AE) as a possible future paradigm for human-robot interaction (HRI).
no code implementations • 17 Aug 2021 • Muraleekrishna Gopinathan, Giang Truong, Jumana Abu-Khalaf
In this work, we present a semantic scene understanding pipeline that fuses 2D and 3D detection branches to generate a semantic map of the environment.