9 citations · 17 across the 5 of their papers we have counts for
5 papers
VIBUS: Data-efficient 3D Scene Parsing with VIewpoint Bottleneck and Uncertainty-Spectrum Modeling
Beiwen Tian, Liyi Luo, Hao Zhao +1
Recently, 3D scenes parsing with deep learning approaches has been a heating topic. However, current methods with fully-supervised models require manually annotated point-wise supe…
TOIST: Task Oriented Instance Segmentation Transformer with Noun-Pronoun Distillation
Pengfei Li, Beiwen Tian, Yongliang Shi +4
Current referring expression comprehension algorithms can effectively detect or segment objects indicated by nouns, but how to understand verb reference is still under-explored. As…
Planning Assembly Sequence with Graph Transformer
Lin Ma, Jiangtao Gong, Hao Xu +4
Assembly sequence planning (ASP) is the essential process for modern manufacturing, proven to be NP-complete thus its effective and efficient solution has been a challenge for rese…
Understanding Embodied Reference with Touch-Line Transformer
Yang Li, Xiaoxue Chen, Hao Zhao +4
We study embodied reference understanding, the task of locating referents using embodied gestural signals and language references. Human studies have revealed that objects referred…
Efficient Robotic Manipulation Through Offline-to-Online Reinforcement Learning and Goal-Aware State Information
Jin Li, Xianyuan Zhan, Zixu Xiao +1
End-to-end learning robotic manipulation with high data efficiency is one of the key challenges in robotics. The latest methods that utilize human demonstration data and unsupervis…