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Gang Sun

7 accepted papers

2025

CLID-SLAM: A Coupled LiDAR-Inertial Neural Implicit Dense SLAM With Region-Specific SDF Estimation

RA-L 2025

This letter proposes a novel scan-to-neural model matching, tightly-coupled LiDAR-inertial Simultaneous Localization and Mapping (SLAM) system, which can achieve more accurate state estimation and incrementally reconstruct the dense map. Different from the existing methods, the key insight of the pr

Cited by 3SourceScholar
2024

MUP-LIO: Mapping Uncertainty-aware Point-wise Lidar Inertial Odometry

IROS 2024poster

This paper proposes a mapping uncertainty-aware point-wise Lidar Inertial Odometry (LIO), which synthesizes the point-wise point-to-plane match and map refreshment into a probabilistic model. As a result, it can address the issue of mismatching during point registration and remove in-frame motion di…

Cited by 0SourceScholar
2024

Wav2SQL: Direct Generalizable Speech-To-SQL Parsing

ACL 2024findings

We release a multi-accent dataset and propose speech-programming and gradient reversal classifier to improve the generalization.Abstract: Speech-to-SQL (S2SQL) aims to convert spoken questions into SQL queries given relational databases, which has been traditionally implemented in a cascaded manner…

Cited by 3SourcePDFScholar
2023

Topology-Guided Perception-Aware Receding Horizon Trajectory Generation for UAVs

IROS 2023poster

The perception-aware motion planning method based on the localization uncertainty has the potential to improve the localization accuracy for robot navigation. How-ever, most of the existing perception-aware methods pre-build a global feature map and can not generate the perception- aware trajectory…

Cited by 1SourceScholar
2018

Gather-Excite: Exploiting Feature Context in Convolutional Neural Networks

NeurIPS 2018poster

While the use of bottom-up local operators in convolutional neural networks (CNNs) matches well some of the statistics of natural images, it may also prevent such models from capturing contextual long-range feature interactions. In this work, we propose a simple, lightweight approach for better cont…