36 citations · 62 across the 13 of their papers we have counts for
13 papers
Flying Co-Stereo: Enabling Long-Range Aerial Dense Mapping via Collaborative Stereo Vision of Dynamic-Baseline
Zhaoying Wang, Xingxing Zuo, Wei Dong
Lightweight long-range mapping is critical for safe navigation of UAV swarms in large-scale unknown environments. Traditional stereo vision systems with fixed short baselines face…
MonoTher-Depth: Enhancing Thermal Depth Estimation via Confidence-Aware Distillation
Xingxing Zuo, Nikhil Ranganathan, Connor Lee +2
Monocular depth estimation (MDE) from thermal images is a crucial technology for robotic systems operating in challenging conditions such as fog, smoke, and low light. The limited…
PG-SLAM: Photo-realistic and Geometry-aware RGB-D SLAM in Dynamic Environments
Haoang Li, Xiangqi Meng, Xingxing Zuo +3
Simultaneous localization and mapping (SLAM) has achieved impressive performance in static environments. However, SLAM in dynamic environments remains an open question. Many method…
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…