image-to-point cloud registration 1lidar upsampling 1pose estimation 1self-supervised learning 1sensor fusion 1
From the 1 of 3 linked papers with an AI index.
3 papers
cs.RO2026
Image-to-Point Cloud Registration Made Easy with Rectified Flow-based LiDAR Upsampling
Reon Tabata, Kenji Koide, Shuji Oishi +4
The paper presents a method that converts a sparse LiDAR scan into a dense intensity image using conditional rectified flow, matches it to a camera image, and estimates the 6‑DoF p…
cs.CV2026
Towards Compact Autonomous Driving Perception with Balanced Learning and Multi-sensor Fusion
Oskar Natan, Jun Miura
We present a novel compact deep multi-task learning model to handle various autonomous driving perception tasks in one forward pass. The model performs multiple views of semantic s…
cs.RO2026
DeepIPCv2: LiDAR-powered Robust Environmental Perception and Navigational Control for Autonomous Vehicle
Oskar Natan, Jun Miura
We propose DeepIPCv2, an end-to-end autonomous driving framework that integrates LiDAR-based environmental perception with command-specific control learning. Unlike prior camera-re…