7 citations · 26 across the 20 of their papers we have counts for
14 papers · 1 filter
MemReg: Streaming Outdoor LiDAR Point Cloud Registration with Hybrid Memory Buffers
Jiuming Liu, Mengmeng Liu, Guangming Wang +6
Prior outdoor LiDAR registration works are commonly limited by the pair-wise input paradigm, which neglects temporal correlations inherent within streaming sequences. In this paper…
DiffSAC: Diffusion-guided Sampling for Consensus-based Robust Estimation
Chang Nie, Guangming Wang, Zhe Liu +1
Robust estimation is a core computer vision task frequently tackled using sample consensus. However, traditional methods suffer from inefficient sampling as they struggle to identi…
RegFormer++: An Efficient Large-Scale 3D LiDAR Point Registration Network with Projection-Aware 2D Transformer
Jiuming Liu, Guangming Wang, Zhe Liu +7
Although point cloud registration has achieved remarkable advances in object-level and indoor scenes, large-scale LiDAR registration methods has been rarely explored before. Challe…
TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation
Jiuming Liu, Zheng Huang, Mengmeng Liu +4
LiDAR scene generation is critical for mitigating real-world LiDAR data collection costs and enhancing the robustness of downstream perception tasks in autonomous driving. However,…
DSLO: Deep Sequence LiDAR Odometry Based on Inconsistent Spatio-temporal Propagation
Huixin Zhang, Guangming Wang, Xinrui Wu +5
This paper introduces a 3D point cloud sequence learning model based on inconsistent spatio-temporal propagation for LiDAR odometry, termed DSLO. It consists of a pyramid structure…
MAMBA4D: Efficient Long-Sequence Point Cloud Video Understanding with Disentangled Spatial-Temporal State Space Models
Jiuming Liu, Jinru Han, Lihao Liu +4
Point cloud videos can faithfully capture real-world spatial geometries and temporal dynamics, which are essential for enabling intelligent agents to understand the dynamically cha…
EMIE-MAP: Large-Scale Road Surface Reconstruction Based on Explicit Mesh and Implicit Encoding
Wenhua Wu, Qi Wang, Guangming Wang +6
Road surface reconstruction plays a vital role in autonomous driving systems, enabling road lane perception and high-precision mapping. Recently, neural implicit encoding has achie…
DVN-SLAM: Dynamic Visual Neural SLAM Based on Local-Global Encoding
Wenhua Wu, Guangming Wang, Ting Deng +5
Recent research on Simultaneous Localization and Mapping (SLAM) based on implicit representation has shown promising results in indoor environments. However, there are still some c…
Point Mamba: A Novel Point Cloud Backbone Based on State Space Model with Octree-Based Ordering Strategy
Jiuming Liu, Ruiji Yu, Yian Wang +4
Recently, state space model (SSM) has gained great attention due to its promising performance, linear complexity, and long sequence modeling ability in both language and image doma…
DVLO: Deep Visual-LiDAR Odometry with Local-to-Global Feature Fusion and Bi-Directional Structure Alignment
Jiuming Liu, Dong Zhuo, Zhiheng Feng +4
Information inside visual and LiDAR data is well complementary derived from the fine-grained texture of images and massive geometric information in point clouds. However, it remain…
3DSFLabelling: Boosting 3D Scene Flow Estimation by Pseudo Auto-labelling
Chaokang Jiang, Guangming Wang, Jiuming Liu +6
Learning 3D scene flow from LiDAR point clouds presents significant difficulties, including poor generalization from synthetic datasets to real scenes, scarcity of real-world 3D la…
Spherical Frustum Sparse Convolution Network for LiDAR Point Cloud Semantic Segmentation
Yu Zheng, Guangming Wang, Jiuming Liu +2
LiDAR point cloud semantic segmentation enables the robots to obtain fine-grained semantic information of the surrounding environment. Recently, many works project the point cloud…
DifFlow3D: Toward Robust Uncertainty-Aware Scene Flow Estimation with Diffusion Model
Jiuming Liu, Guangming Wang, Weicai Ye +6
Scene flow estimation, which aims to predict per-point 3D displacements of dynamic scenes, is a fundamental task in the computer vision field. However, previous works commonly suff…
SC-NeRF: Self-Correcting Neural Radiance Field with Sparse Views
Liang Song, Guangming Wang, Jiuming Liu +3
In recent studies, the generalization of neural radiance fields for novel view synthesis task has been widely explored. However, existing methods are limited to objects and indoor…