36 citations · 107 across the 29 of their papers we have counts for
12 papers · 1 filter
L2COcc: Lightweight Camera-Centric Semantic Scene Completion via Distillation of LiDAR Model
Ruoyu Wang, Yukai Ma, Yi Yao +5
Semantic Scene Completion (SSC) constitutes a pivotal element in autonomous driving perception systems, tasked with inferring the 3D semantic occupancy of a scene from sensory data…
LiCROcc: Teach Radar for Accurate Semantic Occupancy Prediction using LiDAR and Camera
Yukai Ma, Jianbiao Mei, Xuemeng Yang +6
Semantic Scene Completion (SSC) is pivotal in autonomous driving perception, frequently confronted with the complexities of weather and illumination changes. The long-term strategy…
RIDERS: Radar-Infrared Depth Estimation for Robust Sensing
Han Li, Yukai Ma, Yuehao Huang +4
Dense depth recovery is crucial in autonomous driving, serving as a foundational element for obstacle avoidance, 3D object detection, and local path planning. Adverse weather condi…
M2-CLIP: A Multimodal, Multi-task Adapting Framework for Video Action Recognition
Mengmeng Wang, Jiazheng Xing, Boyuan Jiang +6
Recently, the rise of large-scale vision-language pretrained models like CLIP, coupled with the technology of Parameter-Efficient FineTuning (PEFT), has captured substantial attrac…
RadarCam-Depth: Radar-Camera Fusion for Depth Estimation with Learned Metric Scale
Han Li, Yukai Ma, Yaqing Gu +3
We present a novel approach for metric dense depth estimation based on the fusion of a single-view image and a sparse, noisy Radar point cloud. The direct fusion of heterogeneous R…
SimpleMapping: Real-Time Visual-Inertial Dense Mapping with Deep Multi-View Stereo
Yingye Xin, Xingxing Zuo, Dongyue Lu +1
We present a real-time visual-inertial dense mapping method capable of performing incremental 3D mesh reconstruction with high quality using only sequential monocular images and in…
Incremental Dense Reconstruction from Monocular Video with Guided Sparse Feature Volume Fusion
Xingxing Zuo, Nan Yang, Nathaniel Merrill +2
Incrementally recovering 3D dense structures from monocular videos is of paramount importance since it enables various robotics and AR applications. Feature volumes have recently b…
Correlation Pyramid Network for 3D Single Object Tracking
Mengmeng Wang, Teli Ma, Xingxing Zuo +2
3D LiDAR-based single object tracking (SOT) has gained increasing attention as it plays a crucial role in 3D applications such as autonomous driving. The central problem is how to…
High-Quality RGB-D Reconstruction via Multi-View Uncalibrated Photometric Stereo and Gradient-SDF
Lu Sang, Bjoern Haefner, Xingxing Zuo +1
Fine-detailed reconstructions are in high demand in many applications. However, most of the existing RGB-D reconstruction methods rely on pre-calculated accurate camera poses to re…
MBA-VO: Motion Blur Aware Visual Odometry
Peidong Liu, Xingxing Zuo, Viktor Larsson +1
Motion blur is one of the major challenges remaining for visual odometry methods. In low-light conditions where longer exposure times are necessary, motion blur can appear even for…
CodeVIO: Visual-Inertial Odometry with Learned Optimizable Dense Depth
Xingxing Zuo, Nathaniel Merrill, Wei Li +3
In this work, we present a lightweight, tightly-coupled deep depth network and visual-inertial odometry (VIO) system, which can provide accurate state estimates and dense depth map…
Robust Visual SLAM with Point and Line Features
Xingxing Zuo, Xiaojia Xie, Yong Liu +1
In this paper, we develop a robust efficient visual SLAM system that utilizes heterogeneous point and line features. By leveraging ORB-SLAM [1], the proposed system consists of ste…