activity
20192022
most citedASV: Accelerated Stereo Vision System

35 citations · 56 across the 6 of their papers we have counts for

collaborators

7 papers

cs.AR20221 cited

Crescent: Taming Memory Irregularities for Accelerating Deep Point Cloud Analytics

Yu Feng, Gunnar Hammonds, Yiming Gan +1

3D perception in point clouds is transforming the perception ability of future intelligent machines. Point cloud algorithms, however, are plagued by irregular memory accesses, lead…

cs.HC20222 cited

Real-Time Gaze Tracking with Event-Driven Eye Segmentation

Yu Feng, Nathan Goulding-Hotta, Asif Khan +2

Gaze tracking is increasingly becoming an essential component in Augmented and Virtual Reality. Modern gaze tracking al gorithms are heavyweight; they operate at most 5 Hz on mobil…

cs.CV2021

Fast and Accurate: Video Enhancement using Sparse Depth

Yu Feng, Patrick Hansen, Paul N. Whatmough +2

This paper presents a general framework to build fast and accurate algorithms for video enhancement tasks such as super-resolution, deblurring, and denoising. Essential to our fram…

eess.IV20204 cited

Real-Time Spatio-Temporal LiDAR Point Cloud Compression

Yu Feng, Shaoshan Liu, Yuhao Zhu

Compressing massive LiDAR point clouds in real-time is critical to autonomous machines such as drones and self-driving cars. While most of the recent prior work has focused on comp…

cs.CV20203 cited

Mesorasi: Architecture Support for Point Cloud Analytics via Delayed-Aggregation

Yu Feng, Boyuan Tian, Tiancheng Xu +2

Point cloud analytics is poised to become a key workload on battery-powered embedded and mobile platforms in a wide range of emerging application domains, such as autonomous drivin…

cs.CV201935 cited

ASV: Accelerated Stereo Vision System

Yu Feng, Paul Whatmough, Yuhao Zhu

Estimating depth from stereo vision cameras, i.e., "depth from stereo", is critical to emerging intelligent applications deployed in energy- and performance-constrained devices, su…