Search Results for author: Yongliang Shi

Found 6 papers, 4 papers with code

LODE: Locally Conditioned Eikonal Implicit Scene Completion from Sparse LiDAR

1 code implementation27 Feb 2023 Pengfei Li, Ruowen Zhao, Yongliang Shi, Hao Zhao, Jirui Yuan, Guyue Zhou, Ya-Qin Zhang

In this paper, we propose a novel Eikonal formulation that conditions the implicit representation on localized shape priors which function as dense boundary value constraints, and demonstrate it works on SemanticKITTI and SemanticPOSS.

Autonomous Driving Representation Learning

TOIST: Task Oriented Instance Segmentation Transformer with Noun-Pronoun Distillation

1 code implementation19 Oct 2022 Pengfei Li, Beiwen Tian, Yongliang Shi, Xiaoxue Chen, Hao Zhao, Guyue Zhou, Ya-Qin Zhang

As such, we study the challenging problem of task oriented detection, which aims to find objects that best afford an action indicated by verbs like sit comfortably on.

Instance Segmentation Referring Expression +2

City-scale Incremental Neural Mapping with Three-layer Sampling and Panoptic Representation

no code implementations28 Sep 2022 Yongliang Shi, Runyi Yang, Pengfei Li, Zirui Wu, Hao Zhao, Guyue Zhou

Neural implicit representations are drawing a lot of attention from the robotics community recently, as they are expressive, continuous and compact.

LATITUDE: Robotic Global Localization with Truncated Dynamic Low-pass Filter in City-scale NeRF

1 code implementation18 Sep 2022 Zhenxin Zhu, Yuantao Chen, Zirui Wu, Chao Hou, Yongliang Shi, Chuxuan Li, Pengfei Li, Hao Zhao, Guyue Zhou

In this paper, we present LATITUDE: Global Localization with Truncated Dynamic Low-pass Filter, which introduces a two-stage localization mechanism in city-scale NeRF.

Pose Prediction

Semi-supervised Implicit Scene Completion from Sparse LiDAR

1 code implementation29 Nov 2021 Pengfei Li, Yongliang Shi, Tianyu Liu, Hao Zhao, Guyue Zhou, Ya-Qin Zhang

Recent advances show that semi-supervised implicit representation learning can be achieved through physical constraints like Eikonal equations.

Representation Learning

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