43 citations · 48 across the 14 of their papers we have counts for
7 papers · 1 filter
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…
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…
ThermoStereoRT: Thermal Stereo Matching in Real Time via Knowledge Distillation and Attention-based Refinement
Anning Hu, Ang Li, Xirui Jin +1
We introduce ThermoStereoRT, a real-time thermal stereo matching method designed for all-weather conditions that recovers disparity from two rectified thermal stereo images, envisi…
Head-Aware KV Cache Compression for Efficient Visual Autoregressive Modeling
Ziran Qin, Youru Lv, Mingbao Lin +4
Visual Autoregressive (VAR) models adopt a next-scale prediction paradigm, offering high-quality content generation with substantially fewer decoding steps. However, existing VAR m…
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…