Wenhu Chen, Ph.D. Receives Best Paper Award - Honorable Mention
By Natalia Diaz Amabilis, PR Assistant
Wenhu Chen is a fourth-year Ph.D. student at the University of California, Santa Barbara, advised by William Yang Wang and Xifeng Yan. Chen received a competitive “Best Student Paper Award - Honorable Mention” from WACV 2021. WACV is the premier international computer vision event comprising the main conference and several co-located workshops and tutorials. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.
The paper submission is joint work with his Microsoft mentors on meta module networks for grounded question answering. Wenhu proposed Meta Module Network (MMN) centered on a novel meta module, which can take in function recipes and morph into diverse instance modules dynamically. The instance modules are then woven into an execution graph for complex visual reasoning, inheriting the strong explainability and compositionality of NMN. With such a flexible instantiation mechanism, the parameters of instance modules are inherited from the central meta module, retaining the same model complexity as the function set grows, which promises better scalability. Meanwhile, as functions are encoded into the embedding space, unseen functions can be readily represented based on its structural similarity with previously observed ones, which ensures better generalizability.
Chen’s research interests cover natural language processing, deep learning, and knowledge representation. Specifically, he aims at developing models that can ground and reason over external world knowledge to understand human language and communicate with humans. He is also interested in multi-modal problems such as visual question answering and image/video captioning.
Congratulations to Wenhu! UCSB is excited to see what he accomplishes in the future as he enters the job market this year!