1 citations · 2 across the 14 of their papers we have counts for
14 papers
KLTNet: Learning Sparse Feature Tracking for Robust and Accurate Monocular Visual-Inertial Odometry
Renbiao Jin, Danping Zou, Wenxian Yu
Many feature-based visual-inertial odometry (VIO) systems rely on sparse feature tracking, whose accuracy and robustness directly affect state estimation. Classical KLT trackers re…
RealVDeblur: One-Step Diffusion for Generalizable Real-World Video Deblurring
Renbiao Jin, Mingxin Yang, Yutian Chen +8
Real-world video deblurring remains challenging due to diverse motion patterns, complex degradations, and the scarcity of realistic training data, yet robust restoration is critica…
Learning Agile Navigation in Crowded Environments for Quadruped Robots
Shuyu Wu, Zeyu Liu, Tianbao Zhang +6
Navigating dynamic and crowded environments presents significant challenges for quadruped robots due to severe sensor occlusion and unpredictable human motion. Existing approaches…
Simple but Stable, Fast and Safe: Achieve End-to-end Control by High-Fidelity Differentiable Simulation
Fanxing Li, Shengyang Wang, Yuxiang Huang +5
Obstacle avoidance is a fundamental vision-based task essential for enabling quadrotors to perform advanced applications. When planning the trajectory, existing approaches both on…
E2E-Fly: An Integrated Training-to-Deployment System for End-to-End Quadrotor Autonomy
Fangyu Sun, Fanxing Li, Linzuo Zhang +5
Training and transferring learning-based policies for quadrotors from simulation to reality remains challenging due to inefficient visual rendering, physical modeling inaccuracies,…
Vision-Based End-to-End Learning for UAV Traversal of Irregular Gaps via Differentiable Simulation
Linzuo Zhang, Yu Hu, Feng Yu +3
-Navigation through narrow and irregular gaps is an essential skill in autonomous drones for applications such as inspection, search-and-rescue, and disaster response. However, tra…
VisFly-Lab: Unified Differentiable Framework for First-Order Reinforcement Learning of Quadrotor Control
Fanxing Li, Fangyu Sun, Tianbao Zhang +5
First-order reinforcement learning with differentiable simulation is promising for quadrotor control, but practical progress remains fragmented across task-specific settings. To su…
Curriculum Reinforcement Learning for Quadrotor Racing with Random Obstacles
Fangyu Sun, Fanxing Li, Yu Hu +4
Autonomous drone racing has attracted increasing interest as a research topic for exploring the limits of agile flight. However, existing studies primarily focus on obstacle-free r…
CoordAR: One-Reference 6D Pose Estimation of Novel Objects via Autoregressive Coordinate Map Generation
Dexin Zuo, Ang Li, Wei Wang +2
Object 6D pose estimation, a crucial task for robotics and augmented reality applications, becomes particularly challenging when dealing with novel objects whose 3D models are not…
PlanarGS: High-Fidelity Indoor 3D Gaussian Splatting Guided by Vision-Language Planar Priors
Xirui Jin, Renbiao Jin, Boying Li +2
Three-dimensional Gaussian Splatting (3DGS) has recently emerged as an efficient representation for novel-view synthesis, achieving impressive visual quality. However, in scenes do…
StableTracker: Learning to Stably Track Target via Differentiable Simulation
Fanxing Li, Shengyang Wang, Fangyu Sun +5
Existing FPV object tracking methods heavily rely on handcrafted modular pipelines, which incur high onboard computation and cumulative errors. While learning-based approaches have…
Seeing Through Pixel Motion: Learning Obstacle Avoidance from Optical Flow with One Camera
Yu Hu, Yuang Zhang, Yunlong Song +6
Optical flow captures the motion of pixels in an image sequence over time, providing information about movement, depth, and environmental structure. Flying insects utilize this inf…
Stereo-LiDAR Depth Estimation with Deformable Propagation and Learned Disparity-Depth Conversion
Ang Li, Anning Hu, Wei Xi +2
Accurate and dense depth estimation with stereo cameras and LiDAR is an important task for automatic driving and robotic perception. While sparse hints from LiDAR points have impro…
Ground-Fusion: A Low-cost Ground SLAM System Robust to Corner Cases
Jie Yin, Ang Li, Wei Xi +2
We introduce Ground-Fusion, a low-cost sensor fusion simultaneous localization and mapping (SLAM) system for ground vehicles. Our system features efficient initialization, effectiv…