activity
20192023
most citedHR-Depth: High Resolution Self-Supervised Monocular Depth Estimation

24 citations · 81 across the 10 of their papers we have counts for

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8 papers · 1 filter

cs.CV2023★ 1 cited

vMAP: Vectorised Object Mapping for Neural Field SLAM

Xin Kong, Shikun Liu, Marwan Taher +1

We present vMAP, an object-level dense SLAM system using neural field representations. Each object is represented by a small MLP, enabling efficient, watertight object modelling wi…

cs.CV2021★ 4 cited

Semantic Segmentation-assisted Scene Completion for LiDAR Point Clouds

Xuemeng Yang, Hao Zou, Xin Kong +5

Outdoor scene completion is a challenging issue in 3D scene understanding, which plays an important role in intelligent robotics and autonomous driving. Due to the sparsity of LiDA…

cs.CV2021★ 2 cited

SSC: Semantic Scan Context for Large-Scale Place Recognition

Lin Li, Xin Kong, Xiangrui Zhao +2

Place recognition gives a SLAM system the ability to correct cumulative errors. Unlike images that contain rich texture features, point clouds are almost pure geometric information…

cs.CV2020★ 24 cited

HR-Depth: High Resolution Self-Supervised Monocular Depth Estimation

Xiaoyang Lyu, Liang Liu, Mengmeng Wang +5

Self-supervised learning shows great potential in monoculardepth estimation, using image sequences as the only source ofsupervision. Although people try to use the high-resolutioni…

cs.CV2020★ 10 cited

FlowMOT: 3D Multi-Object Tracking by Scene Flow Association

Guangyao Zhai, Xin Kong, Jinhao Cui +2

Most end-to-end Multi-Object Tracking (MOT) methods face the problems of low accuracy and poor generalization ability. Although traditional filter-based methods can achieve better…

cs.CV2020★ 3 cited

F-Siamese Tracker: A Frustum-based Double Siamese Network for 3D Single Object Tracking

Hao Zou, Jinhao Cui, Xin Kong +4

This paper presents F-Siamese Tracker, a novel approach for single object tracking prominently characterized by more robustly integrating 2D and 3D information to reduce redundant…

cs.CV2020★ 6 cited

Semantic Graph Based Place Recognition for 3D Point Clouds

Xin Kong, Xuemeng Yang, Guangyao Zhai +6

Due to the difficulty in generating the effective descriptors which are robust to occlusion and viewpoint changes, place recognition for 3D point cloud remains an open issue. Unlik…

cs.CV2019★ 13 cited

PASS3D: Precise and Accelerated Semantic Segmentation for 3D Point Cloud

Xin Kong, Guangyao Zhai, Baoquan Zhong +1

In this paper, we propose PASS3D to achieve point-wise semantic segmentation for 3D point cloud. Our framework combines the efficiency of traditional geometric methods with robustn…