501 citations · 1.9k across the 56 of their papers we have counts for
56 papers
Novel Diffusion Models for Multimodal 3D Hand Trajectory Prediction
Junyi Ma, Wentao Bao, Jingyi Xu +3
Predicting hand motion is critical for understanding human intentions and bridging the action space between human movements and robot manipulations. Existing hand trajectory predic…
UGNA-VPR: A Novel Training Paradigm for Visual Place Recognition Based on Uncertainty-Guided NeRF Augmentation
Yehui Shen, Lei Zhang, Qingqiu Li +4
Visual place recognition (VPR) is crucial for robots to identify previously visited locations, playing an important role in autonomous navigation in both indoor and outdoor environ…
ResLPR: A LiDAR Data Restoration Network and Benchmark for Robust Place Recognition Against Weather Corruptions
Wenqing Kuang, Xiongwei Zhao, Yehui Shen +4
LiDAR-based place recognition (LPR) is a key component for autonomous driving, and its resilience to environmental corruption is critical for safety in high-stakes applications. Wh…
RING#: PR-by-PE Global Localization with Roto-translation Equivariant Gram Learning
Sha Lu, Xuecheng Xu, Yuxuan Wu +4
Global localization using onboard perception sensors, such as cameras and LiDARs, is crucial in autonomous driving and robotics applications when GPS signals are unreliable. Most a…
NeuroVE: Brain-inspired Linear-Angular Velocity Estimation with Spiking Neural Networks
Xiao Li, Xieyuanli Chen, Ruibin Guo +4
Vision-based ego-velocity estimation is a fundamental problem in robot state estimation. However, the constraints of frame-based cameras, including motion blur and insufficient fra…
CV-MOS: A Cross-View Model for Motion Segmentation
Xiaoyu Tang, Zeyu Chen, Jintao Cheng +3
In autonomous driving, accurately distinguishing between static and moving objects is crucial for the autonomous driving system. When performing the motion object segmentation (MOS…
GOReloc: Graph-based Object-Level Relocalization for Visual SLAM
Yutong Wang, Chaoyang Jiang, Xieyuanli Chen
This article introduces a novel method for object-level relocalization of robotic systems. It determines the pose of a camera sensor by robustly associating the object detections i…
BEVPlace++: Fast, Robust, and Lightweight LiDAR Global Localization for Unmanned Ground Vehicles
Lun Luo, Si-Yuan Cao, Xiaorui Li +4
This article introduces BEVPlace++, a novel, fast, and robust LiDAR global localization method for unmanned ground vehicles. It uses lightweight convolutional neural networks (CNNs…
SGLC: Semantic Graph-Guided Coarse-Fine-Refine Full Loop Closing for LiDAR SLAM
Neng Wang, Xieyuanli Chen, Chenghao Shi +3
Loop closing is a crucial component in SLAM that helps eliminate accumulated errors through two main steps: loop detection and loop pose correction. The first step determines wheth…
TD-NeRF: Novel Truncated Depth Prior for Joint Camera Pose and Neural Radiance Field Optimization
Zhen Tan, Zongtan Zhou, Yangbing Ge +3
The reliance on accurate camera poses is a significant barrier to the widespread deployment of Neural Radiance Fields (NeRF) models for 3D reconstruction and SLAM tasks. The existi…
Diff-IP2D: Diffusion-Based Hand-Object Interaction Prediction on Egocentric Videos
Junyi Ma, Jingyi Xu, Xieyuanli Chen +1
Understanding how humans would behave during hand-object interaction is vital for applications in service robot manipulation and extended reality. To achieve this, some recent work…
Diffusion-Based Point Cloud Super-Resolution for mmWave Radar Data
Kai Luan, Chenghao Shi, Neng Wang +3
The millimeter-wave radar sensor maintains stable performance under adverse environmental conditions, making it a promising solution for all-weather perception tasks, such as outdo…
TSCM: A Teacher-Student Model for Vision Place Recognition Using Cross-Metric Knowledge Distillation
Yehui Shen, Mingmin Liu, Huimin Lu +1
Visual place recognition (VPR) plays a pivotal role in autonomous exploration and navigation of mobile robots within complex outdoor environments. While cost-effective and easily d…
ModaLink: Unifying Modalities for Efficient Image-to-PointCloud Place Recognition
Weidong Xie, Lun Luo, Nanfei Ye +7
Place recognition is an important task for robots and autonomous cars to localize themselves and close loops in pre-built maps. While single-modal sensor-based methods have shown s…
RadarMOSEVE: A Spatial-Temporal Transformer Network for Radar-Only Moving Object Segmentation and Ego-Velocity Estimation
Changsong Pang, Xieyuanli Chen, Yimin Liu +2
Moving object segmentation (MOS) and Ego velocity estimation (EVE) are vital capabilities for mobile systems to achieve full autonomy. Several approaches have attempted to achieve…
MF-MOS: A Motion-Focused Model for Moving Object Segmentation
Jintao Cheng, Kang Zeng, Zhuoxu Huang +5
Moving object segmentation (MOS) provides a reliable solution for detecting traffic participants and thus is of great interest in the autonomous driving field. Dynamic capture is a…
Cam4DOcc: Benchmark for Camera-Only 4D Occupancy Forecasting in Autonomous Driving Applications
Junyi Ma, Xieyuanli Chen, Jiawei Huang +6
Understanding how the surrounding environment changes is crucial for performing downstream tasks safely and reliably in autonomous driving applications. Recent occupancy estimation…
Mobile-Seed: Joint Semantic Segmentation and Boundary Detection for Mobile Robots
Youqi Liao, Shuhao Kang, Jianping Li +5
Precise and rapid delineation of sharp boundaries and robust semantics is essential for numerous downstream robotic tasks, such as robot grasping and manipulation, real-time semant…
Fast and Accurate Deep Loop Closing and Relocalization for Reliable LiDAR SLAM
Chenghao Shi, Xieyuanli Chen, Junhao Xiao +2
Loop closing and relocalization are crucial techniques to establish reliable and robust long-term SLAM by addressing pose estimation drift and degeneration. This article begins by…
CoFiI2P: Coarse-to-Fine Correspondences for Image-to-Point Cloud Registration
Shuhao Kang, Youqi Liao, Jianping Li +7
Image-to-point cloud (I2P) registration is a fundamental task for robots and autonomous vehicles to achieve cross-modality data fusion and localization. Current I2P registration me…
TFNet: Exploiting Temporal Cues for Fast and Accurate LiDAR Semantic Segmentation
Rong Li, ShiJie Li, Xieyuanli Chen +3
LiDAR semantic segmentation plays a crucial role in enabling autonomous driving and robots to understand their surroundings accurately and robustly. A multitude of methods exist wi…
Building Volumetric Beliefs for Dynamic Environments Exploiting Map-Based Moving Object Segmentation
Benedikt Mersch, Tiziano Guadagnino, Xieyuanli Chen +3
Mobile robots that navigate in unknown environments need to be constantly aware of the dynamic objects in their surroundings for mapping, localization, and planning. It is key to r…
PowerBEV: A Powerful Yet Lightweight Framework for Instance Prediction in Bird's-Eye View
Peizheng Li, Shuxiao Ding, Xieyuanli Chen +3
Accurately perceiving instances and predicting their future motion are key tasks for autonomous vehicles, enabling them to navigate safely in complex urban traffic. While bird's-ey…
Deep Reinforcement Learning for Flipper Control of Tracked Robots
Hainan Pan, Bailiang Chen, Kaihong Huang +3
The autonomous control of flippers plays an important role in enhancing the intelligent operation of tracked robots within complex environments. While existing methods mainly rely…