Compositional neural scene graph studies have shown that radiance fields...
With significant annotation savings, point supervision has been proven
e...
Nowadays, many visual scene understanding problems are addressed by dens...
Touch is an important channel for human-robot interaction, while it is
c...
The development of Autonomous Vehicle (AV) has created a novel job, the
...
As autonomous driving systems prevail, it is becoming increasingly criti...
Guiding robots, in the form of canes or cars, have recently been explore...
Children are one of the groups most influenced by COVID-19-related socia...
Large-scale radiance fields are promising mapping tools for smart
transp...
Recently, 3D scenes parsing with deep learning approaches has been a hea...
This paper proposes a high-fidelity simulation framework that can estima...
Bionic robots are generally considered to have strong flexibility,
adapt...
Assembly sequence planning (ASP) is the essential process for modern
man...
We address the new problem of language-guided semantic style transfer of...
Offline imitation learning (IL) is a powerful method to solve decision-m...
Learning effective reinforcement learning (RL) policies to solve real-wo...
Detecting 3D keypoints from point clouds is important for shape
reconstr...
Multi-task indoor scene understanding is widely considered as an intrigu...
Heated debates continue over the best autonomous driving framework. The
...
End-to-end learning robotic manipulation with high data efficiency is on...
Semantic understanding of 3D point clouds is important for various robot...
3D scene understanding from point clouds plays a vital role for various
...
In this paper a binary feature based Loop Closure Detection (LCD) method...
Aiming at automatic, convenient and non-instrusive motion capture, this ...
Towards robust and convenient indoor shopping mall navigation, we propos...