Publications (7)
Threat-Aware UAV Dodging of Human-Thrown Projectiles with an RGB-D Camera
Yuying Zhang, Na Fan, Haowen Zheng +4
Uncrewed aerial vehicles (UAVs) performing tasks such as transportation and aerial photography are vulnerable to intentional projectile attacks from humans. Dodging such a sudden a…
Design and Implementation of a High-Precision Wind-Estimation UAV with Onboard Sensors
Haowen Yu, Na Fan, Xing Liu +1
Accurate real-time wind vector estimation is essential for enhancing the safety, navigation accuracy, and energy efficiency of unmanned aerial vehicles (UAVs). Traditional approach…
Yet Even Less Is Even Better For Agentic, Reasoning, and Coding LLMs
CodeArts Model Team, Yang Ye, Jingyuan Tan +24
Training effective software engineering agents requires large volumes of task-specific trajectories, incurring substantial data construction costs. Inspired by the "Less-Is-More" h…
FlyAware: Inertia-Aware Aerial Manipulation via Vision-Based Estimation and Post-Grasp Adaptation
Biyu Ye, Na Fan, Zhengping Fan +4
Aerial manipulators (AMs) are gaining increasing attention in automated transportation and emergency services due to their superior dexterity compared to conventional multirotor dr…
Shape from Polarization for Complex Scenes in the Wild
Chenyang Lei, Chenyang Qi, Jiaxin Xie +3
We present a new data-driven approach with physics-based priors to scene-level normal estimation from a single polarization image. Existing shape from polarization (SfP) works main…
Stereo Waterdrop Removal with Row-wise Dilated Attention
Zifan Shi, Na Fan, Dit-Yan Yeung +1
Existing vision systems for autonomous driving or robots are sensitive to waterdrops adhered to windows or camera lenses. Most recent waterdrop removal approaches take a single ima…
Joint Depth and Normal Estimation from Real-world Time-of-flight Raw Data
Rongrong Gao, Na Fan, Changlin Li +2
We present a novel approach to joint depth and normal estimation for time-of-flight (ToF) sensors. Our model learns to predict the high-quality depth and normal maps jointly from T…