501 citations · 1.9k across the 56 of their papers we have counts for
31 papers · 1 filter
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…
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…
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…
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…
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…
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…
RDMNet: Reliable Dense Matching Based Point Cloud Registration for Autonomous Driving
Chenghao Shi, Xieyuanli Chen, Huimin Lu +3
Point cloud registration is an important task in robotics and autonomous driving to estimate the ego-motion of the vehicle. Recent advances following the coarse-to-fine manner show…
NeRF-LOAM: Neural Implicit Representation for Large-Scale Incremental LiDAR Odometry and Mapping
Junyuan Deng, Xieyuanli Chen, Songpengcheng Xia +4
Simultaneously odometry and mapping using LiDAR data is an important task for mobile systems to achieve full autonomy in large-scale environments. However, most existing LiDAR-base…
InsMOS: Instance-Aware Moving Object Segmentation in LiDAR Data
Neng Wang, Chenghao Shi, Ruibin Guo +3
Identifying moving objects is a crucial capability for autonomous navigation, consistent map generation, and future trajectory prediction of objects. In this paper, we propose a no…
CCL: Continual Contrastive Learning for LiDAR Place Recognition
Jiafeng Cui, Xieyuanli Chen
Place recognition is an essential and challenging task in loop closing and global localization for robotics and autonomous driving applications. Benefiting from the recent advances…
CVTNet: A Cross-View Transformer Network for Place Recognition Using LiDAR Data
Junyi Ma, Guangming Xiong, Jingyi Xu +1
LiDAR-based place recognition (LPR) is one of the most crucial components of autonomous vehicles to identify previously visited places in GPS-denied environments. Most existing LPR…
SuperFusion: Multilevel LiDAR-Camera Fusion for Long-Range HD Map Generation
Hao Dong, Weihao Gu, Xianjing Zhang +5
High-definition (HD) semantic map generation of the environment is an essential component of autonomous driving. Existing methods have achieved good performance in this task by fus…
Learning-Based Dimensionality Reduction for Computing Compact and Effective Local Feature Descriptors
Hao Dong, Xieyuanli Chen, Mihai Dusmanu +3
A distinctive representation of image patches in form of features is a key component of many computer vision and robotics tasks, such as image matching, image retrieval, and visual…
SeqOT: A Spatial-Temporal Transformer Network for Place Recognition Using Sequential LiDAR Data
Junyi Ma, Xieyuanli Chen, Jingyi Xu +1
Place recognition is an important component for autonomous vehicles to achieve loop closing or global localization. In this paper, we tackle the problem of place recognition based…