30 citations · 206 across the 67 of their papers we have counts for
14 papers · 1 filter
Self-Aligning Depth-regularized Radiance Fields for Asynchronous RGB-D Sequences
Yuxin Huang, Andong Yang, Zirui Wu +6
It has been shown that learning radiance fields with depth rendering and depth supervision can effectively promote the quality and convergence of view synthesis. However, this para…
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…
Evaluation of Pedestrian Safety in a High-Fidelity Simulation Environment Framework
Lin Ma, Longrui Chen, Yan Zhang +9
Pedestrians' safety is a crucial factor in assessing autonomous driving scenarios. However, pedestrian safety evaluation is rarely considered by existing autonomous driving simulat…
Can Quadruped Navigation Robots be Used as Guide Dogs?
Luyao Wang, Qihe Chen, Yan Zhang +5
Quadruped robots have the potential to guide blind and low vision (BLV) people due to their highly flexible locomotion and emotional value provided by their bionic forms. However,…
City-scale Incremental Neural Mapping with Three-layer Sampling and Panoptic Representation
Yongliang Shi, Runyi Yang, Pengfei Li +3
Neural implicit representations are drawing a lot of attention from the robotics community recently, as they are expressive, continuous and compact. However, city-scale continual i…
LATITUDE: Robotic Global Localization with Truncated Dynamic Low-pass Filter in City-scale NeRF
Zhenxin Zhu, Yuantao Chen, Zirui Wu +6
Neural Radiance Fields (NeRFs) have made great success in representing complex 3D scenes with high-resolution details and efficient memory. Nevertheless, current NeRF-based pose es…
Distance-Aware Occlusion Detection with Focused Attention
Yang Li, Yucheng Tu, Xiaoxue Chen +2
For humans, understanding the relationships between objects using visual signals is intuitive. For artificial intelligence, however, this task remains challenging. Researchers have…
Language-guided Semantic Style Transfer of 3D Indoor Scenes
Bu Jin, Beiwen Tian, Hao Zhao +1
We address the new problem of language-guided semantic style transfer of 3D indoor scenes. The input is a 3D indoor scene mesh and several phrases that describe the target scene. F…
Discriminator-Guided Model-Based Offline Imitation Learning
Wenjia Zhang, Haoran Xu, Haoyi Niu +5
Offline imitation learning (IL) is a powerful method to solve decision-making problems from expert demonstrations without reward labels. Existing offline IL methods suffer from sev…
When to Trust Your Simulator: Dynamics-Aware Hybrid Offline-and-Online Reinforcement Learning
Haoyi Niu, Shubham Sharma, Yiwen Qiu +4
Learning effective reinforcement learning (RL) policies to solve real-world complex tasks can be quite challenging without a high-fidelity simulation environment. In most cases, we…
SNAKE: Shape-aware Neural 3D Keypoint Field
Chengliang Zhong, Peixing You, Xiaoxue Chen +6
Detecting 3D keypoints from point clouds is important for shape reconstruction, while this work investigates the dual question: can shape reconstruction benefit 3D keypoint detecti…