4 citations · 8 across the 42 of their papers we have counts for
51 papers
VeriCalib: Verifiable Target-Based LiDAR-Camera Calibration
Xiangcheng Hu, Xieyuanli Chen, Feiyi Chen +8
Target-based extrinsic calibration estimates the rigid transform between sensors from a few observations of a known target, and its result is commonly assessed by the root-mean-squ…
Let the Mind Conceive, Let the Hand Achieve: Following Multimodal Instructions for Long-Horizon Robotic Manipulation
Youpeng Wen, Gang Wang, Tianyu Huang +5
A robot following a multi-step instruction needs to act on the right objects in the right order, even as the scene changes. It must also maintain awareness of task progress and det…
LAG-IO: Multi-IMU State Estimation for Legged Robots Using Factor Graphs
Yicheng Zhou, Longwen Chen, Qinghua Yu +3
Robust proprioceptive state estimation is crucial for legged robots, particularly in challenging environments where exteroceptive sensors are unreliable. While traditional leg odom…
The Midas Touch for Metric Depth: Interpretable Metricization for Generalizable Depth Perception
Mengtan Zhang, Yu Ma, Shiqi Jiang +6
Recent foundation models have drastically improved the generalization of monocular relative depth estimation, yet recovering accurate metric depth from their estimates for depth pe…
GWAM: World Action Models for Efficient and Geometry Grounded Image-Goal Navigation
Ke Gui, Chenghao Shi, Ziyue Wang +3
World models capture environment dynamics and support counterfactual reasoning for planning. In image-goal navigation, where the target often lies beyond the current field of view,…
Behavior-Skill: A Fine-Grained Benchmark for Evaluating Vision-Language-Action Policies in Long-Horizon Tasks
Chunyun Ma, Lun Luo, Xingjian Luo +7
Reliable execution of long-horizon mobile manipulation tasks remains challenging because overall task success depends on the successful completion of multiple constituent skills. E…
SIPTraj: Map-Free End-to-End Trajectory Prediction via Physics-Guided Scene Interaction
Feifei Liu, Zejun Wei, Haozhe Wang +6
Trajectory prediction of surrounding agents is a prerequisite for safe planning and decision making in autonomous driving. Without high-definition (HD) maps, sensor-derived bird's-…
G2IA: Geometry-Guided Instance-Aware Retrieval and Refinement for Cross-Modal Place Recognition
Xianyun Jiao, Jingyi Xu, Zhongmiao Yan +2
Cross-modal place recognition (CMPR) enables camera-only robots to localize against pre-built LiDAR maps in autonomous navigation scenarios. This image-to-point-cloud setting is ch…
ParkingTransformer: LLM-Enhanced End-to-End Trajectory Planning for Autonomous Parking
Hauteng Wu, Xu Li, Dong Kong +4
End-to-end autonomous parking has emerged as a critical task within the realm of autonomous driving. However, existing methods suffer from black-box characteristics, lacking high-l…
TOL: Textual Localization with OpenStreetMap
Youqi Liao, Shuhao Kang, Jingyu Xu +6
Natural language provides an intuitive way to express spatial intent in geospatial applications. While existing localization methods often rely on dense point cloud maps or high-re…
GESS: Multi-cue Guided Local Feature Learning via Geometric and Semantic Synergy
Yang Yi, Xieyuanli Chen, Jinpu Zhang +2
Robust local feature detection and description are foundational tasks in computer vision. Existing methods primarily rely on single appearance cues for modeling, leading to unstabl…
MPTF-Net: Multi-view Pyramid Transformer Fusion Network for LiDAR-based Place Recognition
Shuyuan Li, Zihang Wang, Xieyuanli Chen +5
LiDAR-based place recognition (LPR) is essential for global localization and loop-closure detection in large-scale SLAM systems. Existing methods typically construct global descrip…
VLM-Loc: Localization in Point Cloud Maps via Vision-Language Models
Shuhao Kang, Youqi Liao, Peijie Wang +5
Text-to-point-cloud (T2P) localization aims to infer precise spatial positions within 3D point cloud maps from natural language descriptions, reflecting how humans perceive and com…
GeoLoco: Leveraging 3D Geometric Priors from Visual Foundation Model for Robust RGB-Only Humanoid Locomotion
Yufei Liu, Xieyuanli Chen, Hainan Pan +5
The prevailing paradigm of perceptive humanoid locomotion relies heavily on active depth sensors. However, this depth-centric approach fundamentally discards the rich semantic and…
TAPFormer: Robust Arbitrary Point Tracking via Transient Asynchronous Fusion of Frames and Events
Jiaxiong Liu, Zhen Tan, Jinpu Zhang +4
Tracking any point (TAP) is a fundamental yet challenging task in computer vision, requiring high precision and long-term motion reasoning. Recent attempts to combine RGB frames an…
Efficient Point Cloud Processing with High-Dimensional Positional Encoding and Non-Local MLPs
Yanmei Zou, Hongshan Yu, Yaonan Wang +4
Multi-Layer Perceptron (MLP) models are the foundation of contemporary point cloud processing. However, their complex network architectures obscure the source of their strength and…
Training-Free Interaction-Aligned Visual Token Pruning for Efficient Embodied Manipulation
Jintao Cheng, Weibin Li, Haozhe Wang +7
Efficient visual representation is a central image-processing challenge in embodied manipulation, where policies repeatedly process dense visual-token sequences during closed-loop…
SinGeo: Unlock Single Model's Potential for Robust Cross-View Geo-Localization
Yang Chen, Xieyuanli Chen, Junxiang Li +2
Robust cross-view geo-localization (CVGL) remains challenging despite the surge in recent progress. Existing methods still rely on field-of-view (FoV)-specific training paradigms,…
Wild-Drive: Off-Road Scene Captioning and Path Planning via Robust Multi-modal Routing and Efficient Large Language Model
Zihang Wang, Xu Li, Benwu Wang +7
Explainability and transparent decision-making are essential for the safe deployment of autonomous driving systems. Scene captioning summarizes environmental conditions and risk fa…
VGGT-MPR: VGGT-Enhanced Multimodal Place Recognition in Autonomous Driving Environments
Jingyi Xu, Zhangshuo Qi, Zhongmiao Yan +5
In autonomous driving, robust place recognition is critical for global localization and loop closure detection. While inter-modality fusion of camera and LiDAR data in multimodal p…
DST-Calib: A Dual-Path, Self-Supervised, Target-Free LiDAR-Camera Extrinsic Calibration Network
Zhiwei Huang, Yanwei Fu, Yi Zhou +3
LiDAR-camera extrinsic calibration is essential for multi-modal data fusion in robotic perception systems. However, existing approaches typically rely on handcrafted calibration ta…
Diffusion-Based Restoration for Multi-Modal 3D Object Detection in Adverse Weather
Zhijian He, Feifei Liu, Yuwei Li +4
Multi-modal 3D object detection is important for reliable perception in robotics and autonomous driving. However, its effectiveness remains limited under adverse weather conditions…
OMUDA: Omni-level Masking for Unsupervised Domain Adaptation in Semantic Segmentation
Yang Ou, Xiongwei Zhao, Xinye Yang +5
Unsupervised domain adaptation (UDA) enables semantic segmentation models to generalize from a labeled source domain to an unlabeled target domain. However, existing UDA methods st…
LiDAR-VGGT: Cross-Modal Coarse-to-Fine Fusion for Globally Consistent and Metric-Scale Dense Mapping
Lijie Wang, Lianjie Guo, Ziyi Xu +3
Reconstructing large-scale colored point clouds is an important task in robotics, supporting perception, navigation, and scene understanding. Despite advances in LiDAR inertial vis…