Jad Abou-Chakra

Jad Abou-Chakra

Hi there! I am currently pursuing a PhD at the QUT Centre for Robotics where I specialize in perception systems that enable robots to interact with their environments. My current research is dedicated to adapting Neural Radiance Fields and their derivatives to create a real-time, physical representation of the world.

Research

Physically Embodied Gaussian Splatting: Embedding Physical Priors into a Visual 3D World Model For Robotics
Jad Abou-Chakra, Krishan Rana, Feras Dayoub, Niko Suenderhauf
CoRL 2023 - Workshop for Neural Representation Learning for Robot Manipulation
Webpage
X-Embodiment
Open X-Embodiment: Robotic Learning Datasets and RT-X Models
Open X-Embodiment Worldwide Collaboration
Webpage  •   GitHub  •   Paper  •   Datasets  •   Blog Post
ParticleNeRF: Particle based encoding for online neural radiance fields in dynamic scenes
Jad Abou-Chakra, Feras Dayoub, Niko Suenderhauf
★ Best Paper Honorable Mention, WACV ★
Webpage  •   Paper  •   GitHub
SayPlan: Grounding Large Language Models using 3D Scene Graphs for Scalable Robot Task Planning
Krishan Rana, Jesse Haviland, Sourav Garg, Jad Abou-Chakra, Ian Reid, Niko Suenderhauf
★ Oral Presentation, CoRL ★
Webpage  •   Paper  •   Video
Folding By Hand
Learning Fabric Manipulation in the Real World with Human Videos
Robert Lee, Jad Abou-Chakra, Fangyi Zhang, Peter Corke
ICRA 2024
Webpage  •   Dataset  •   Paper
Density-aware NeRF Ensembles
Density-aware NeRF Ensembles: Quantifying Predictive Uncertainty in Neural Radiance Fields
Niko Suenderhauf, Jad Abou-Chakra, Dimity Miller
ICRA 2023
Paper
NeRF
Implicit Object Reconstruction With Noisy Data
Jad Abou-Chakra, Feras Dayoub, Niko Suenderhauf
IMRSS 2022 Workshop
Dataset  •   Paper