Kuo-Hao Zeng 曾國豪

UW Computer Science & Engineering Ph.D. student

khzeng at cs.washington.edu

Bio. I am a Ph.D. student in the Allen School of Computer Science & Engineering at the University of Washington, advised by Prof. Ali Farhadi. My current research interest is in utilizing Visual Reasoning for Robot Learning.

Previously, I reveiced my MS. from National Tsing Hua University, where I worked with Prof. Min Sun on Machine Learning and Deep Learning. We focused their applications to Computer Vision, Natural Language Processing, Robot Learning, and their intersection. During my MS. study, I had the pleasure of being a visiting student working with Dr. Juan Carlos Niebles at Stanford Vision and Learning Lab.

My CV [PDF], last updated Oct. 2018.

PhD. in CSE
Sept. 18 - Now

Visiting in CS
Sept. 16 - Mar. 17

MS. in EE
Sept. 14 - Jul. 17

Summber Intern
Jul. 14 - Sept. 14

BS. in MEM
Sept. 10 - Jun. 14

Summer Intern
Jul. 13 - Aug. 13


Omnidirectional CNN for Visual Place Recognition and Navigation

Hung-Jui Huang, Tsun-Hsuan Wang, Juan-Ting Lin, Chan-Wei Hu, Kuo-Hao Zeng, Min Sun

ICRA 2018

Self-view Grounding Given a Narrated 360° Video

Shih-Han Chou, Yi-Chun Chen, Kuo-Hao Zeng, Hou-Ning Hu, Jianlong Fu, Min Sun

AAAI 2018
ICCV 2017 Workshop

Visual Forecasting by Imitating Dynamics in Natural Sequences

Kuo-Hao Zeng, William B. Shen, De-An Huang, Min Sun, Juan Carlos Niebles

ICCV 2017 Spotlight

Agent-Centric Risk Assessment: Accident Anticipation and Risky Region Localization

Kuo-Hao Zeng, Shih-Han Chou, Fu-Hsiang Chan, Juan Carlos Niebles, Min Sun

CVPR 2017 Spotlight

Leveraging Video Descriptions to Learn Video Question Answering

Kuo-Hao Zeng, Tseng-Hung Chen, Ching-Yao Chuang, Yuan-Hong Liao, Juan Carlos Niebles, Min Sun

AAAI 2017

Title Generation for User Generated Videos

Kuo-Hao Zeng, Tseng-Hung Chen, Juan Carlos Niebles, Min Sun

ECCV 2016

Video Captioning via Sentence Augmentation and Spatio-Temporal Attention

Tseng-Hung Chen, Kuo-Hao Zeng, Wan-Ting Hsu, Min Sun

ACCV 2016 Workshop

Semantic Highlight Retrieval and Term Prediction

Kuo-Hao Zeng, Yen-Chen Lin, Ali Farhadi, Min Sun

TIP 2017
ICIP 2016
CVPR 2015 Workshop

Side Projects

Microsoft - MSR Video to Language Challenge

Microsoft - MSR Video to Language Challenge


MSR Video to Language Challenge is a challenge hosted in ACMMM2016. The challenge mainly facilitates the progress of video captioning.

Computer Vision for Visual Effects

Computer Vision for Visual Effects

Team 11

CVFX is a graduate-level course at NTHU. We made up a team to conduct all the course assignements, term project, and final project.


Spring 2015

Head TA, Signal & System, NTHU

Fall 2015

Head TA, Computer Vision, NTHU