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[CVPR 2025] MASt3R-SLAM: Real-Time Dense SLAM with 3D Reconstruction Priors
A Handy Extrinsic Calibration Tool for LiDAR-camera Systems.
MLNLP: Paper Picture Writing Code
A Fast and Tightly-coupled Sparse-Direct LiDAR-Inertial-Visual Odometry (LIVO).
Autonomous coding agent right in your IDE, capable of creating/editing files, executing commands, using the browser, and more with your permission every step of the way.
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A unified LiDAR-visual system achieving geometrically consistent photorealistic rendering and high-granularity surface reconstruction.
📍PIN-SLAM: LiDAR SLAM Using a Point-Based Implicit Neural Representation for Achieving Global Map Consistency [TRO' 24]
Repository relating to "Reinforcement Learning Meets Visual Odometry" (ECCV, 2024).
LiMo-Calib: On-Site Fast LiDAR-Motor Calibration for Quadruped Robot-Based Panoramic 3D Sensing System
A Collection of LiDAR-Camera-Calibration Papers, Toolboxes and Notes
Postgraduate Thesis: fast_lio_sam + dynamic removal (T-GRS 2024) + multi-session mapping (ICRA 2022 Kim) + object-level update + online relocalization (ICRA 2025) + real-world application (MD-LVIO)
An optimization-based multi-sensor state estimator
USTC FLICAR Dataset (IJRR 2023) 📊 Let’s explore the Embodied Intelligence of large robotic arms 🦾 driven by LIV fusion perception
From anything to mesh like human artists. Official impl. of "MeshAnything V2: Artist-Created Mesh Generation With Adjacent Mesh Tokenization"
CURL: Continuous, Ultra-compact Representation for LiDAR
[ICRA 2025] A MultiModal Mapping (M2Mapping) Framework for Neural Surface Reconstruction and Novel View Synthesis with LiDAR-Visual Systems
A curated list of resources relevant to LiDAR-Visual-Fusion-SLAM
A Robust and Versatile Monocular Visual-Inertial State Estimator
[IEEE TGRS'23] WHU-Helmet: A helmet-based multi-sensor SLAM dataset for the evaluation of real-time 3D mapping in large-scale GNSS-denied environments
T-ESKF: Transformed Error-State Kalman Filter for Consistent Visual-Inertial Navigation
Depth Pro: Sharp Monocular Metric Depth in Less Than a Second.