activity
20172021
most citedMonocular Quasi-Dense 3D Object Tracking

7 citations · 8 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CV20217 cited

Monocular Quasi-Dense 3D Object Tracking

Hou-Ning Hu, Yung-Hsu Yang, Tobias Fischer +3

A reliable and accurate 3D tracking framework is essential for predicting future locations of surrounding objects and planning the observer's actions in numerous applications such…

cs.CV2019

3D LiDAR and Stereo Fusion using Stereo Matching Network with Conditional Cost Volume Normalization

Tsun-Hsuan Wang, Hou-Ning Hu, Chieh Hubert Lin +3

The complementary characteristics of active and passive depth sensing techniques motivate the fusion of the Li-DAR sensor and stereo camera for improved depth perception. Instead o…

cs.CV2018

Self-Supervised Learning of Depth and Camera Motion from 360° Videos

Fu-En Wang, Hou-Ning Hu, Hsien-Tzu Cheng +5

As 360° cameras become prevalent in many autonomous systems (e.g., self-driving cars and drones), efficient 360° perception becomes more and more important. We propose a novel self…

cs.CV2018

Joint Monocular 3D Vehicle Detection and Tracking

Hou-Ning Hu, Qi-Zhi Cai, Dequan Wang +5

Vehicle 3D extents and trajectories are critical cues for predicting the future location of vehicles and planning future agent ego-motion based on those predictions. In this paper,…

cs.CV20171 cited

Self-view Grounding Given a Narrated 360° Video

Shih-Han Chou, Yi-Chun Chen, Kuo-Hao Zeng +3

Narrated 360° videos are typically provided in many touring scenarios to mimic real-world experience. However, previous work has shown that smart assistance (i.e., providing visual…

cs.CV2017

Deep 360 Pilot: Learning a Deep Agent for Piloting through 360° Sports Video

Hou-Ning Hu, Yen-Chen Lin, Ming-Yu Liu +3

Watching a 360° sports video requires a viewer to continuously select a viewing angle, either through a sequence of mouse clicks or head movements. To relieve the viewer from this…