Gnfactor: Multi-task real robot learning with generalizable neural feature fields
It is a long-standing problem in robotics to develop agents capable of executing diverse
manipulation tasks from visual observations in unstructured real-world environments. To …
manipulation tasks from visual observations in unstructured real-world environments. To …
Semantically-aware Neural Radiance Fields for Visual Scene Understanding: A Comprehensive Review
TAQ Nguyen, A Bourki, M Macudzinski… - arXiv preprint arXiv …, 2024 - arxiv.org
This review thoroughly examines the role of semantically-aware Neural Radiance Fields
(NeRFs) in visual scene understanding, covering an analysis of over 250 scholarly papers. It …
(NeRFs) in visual scene understanding, covering an analysis of over 250 scholarly papers. It …
DFields: Dynamic 3D Descriptor Fields for Zero-Shot Generalizable Robotic Manipulation
Scene representation has been a crucial design choice in robotic manipulation systems. An
ideal representation should be 3D, dynamic, and semantic to meet the demands of diverse …
ideal representation should be 3D, dynamic, and semantic to meet the demands of diverse …
Manigaussian: Dynamic gaussian splatting for multi-task robotic manipulation
Performing language-conditioned robotic manipulation tasks in unstructured environments
is highly demanded for general intelligent robots. Conventional robotic manipulation …
is highly demanded for general intelligent robots. Conventional robotic manipulation …
Reconstructive latent-space neural radiance fields for efficient 3d scene representations
T Aumentado-Armstrong, A Mirzaei… - arXiv preprint arXiv …, 2023 - arxiv.org
Neural Radiance Fields (NeRFs) have proven to be powerful 3D representations, capable of
high quality novel view synthesis of complex scenes. While NeRFs have been applied to …
high quality novel view synthesis of complex scenes. While NeRFs have been applied to …
NeRF in Robotics: A Survey
Meticulous 3D environment representations have been a longstanding goal in computer
vision and robotics fields. The recent emergence of neural implicit representations has …
vision and robotics fields. The recent emergence of neural implicit representations has …
Reinforcement Learning with Generalizable Gaussian Splatting
J Wang, Q Zhang, J Sun, J Cao, Y Shao… - arXiv preprint arXiv …, 2024 - arxiv.org
An excellent representation is crucial for reinforcement learning (RL) performance,
especially in vision-based reinforcement learning tasks. The quality of the environment …
especially in vision-based reinforcement learning tasks. The quality of the environment …
Dnact: Diffusion guided multi-task 3d policy learning
This paper presents DNAct, a language-conditioned multi-task policy framework that
integrates neural rendering pre-training and diffusion training to enforce multi-modality …
integrates neural rendering pre-training and diffusion training to enforce multi-modality …
Robo360: A 3D Omnispective Multi-Material Robotic Manipulation Dataset
Building robots that can automate labor-intensive tasks has long been the core motivation
behind the advancements in computer vision and the robotics community. Recent interest in …
behind the advancements in computer vision and the robotics community. Recent interest in …