Search Results for author: Zixuan Chen

Found 6 papers, 3 papers with code

Layered Neighborhood Expansion for Incremental Multiple Graph Matching

1 code implementation ECCV 2020 Zixuan Chen, Zhihui Xie, Junchi Yan Yinqiang Zheng, Xiaokang Yang

In this paper, we treat the graphs as graphs on a super-graph, and propose a novel breadth first search based method for expanding the neighborhood on the super-graph for a new coming graph, such that the matching with the new graph can be efficiently performed within the constructed neighborhood.

Graph Matching

Semantic Segmentation on VSPW Dataset through Aggregation of Transformer Models

no code implementations3 Sep 2021 Zixuan Chen, Junhong Zou, Xiaotao Wang

Semantic segmentation is an important task in computer vision, from which some important usage scenarios are derived, such as autonomous driving, scene parsing, etc.

Autonomous Driving Scene Parsing +2

Revamp: Enhancing Accessible Information Seeking Experience of Online Shopping for Blind or Low Vision Users

no code implementations1 Feb 2021 Ruolin Wang, Zixuan Chen, Mingrui "Ray" Zhang, Zhaoheng Li, Zhixiu Liu, Zihan Dang, Chun Yu, Xiang "Anthony" Chen

Online shopping has become a valuable modern convenience, but blind or low vision (BLV) users still face significant challenges using it, because of: 1) inadequate image descriptions and 2) the inability to filter large amounts of information using screen readers.

Information Retrieval Question Answering +1

Thinking in Frequency: Face Forgery Detection by Mining Frequency-aware Clues

2 code implementations ECCV 2020 Yuyang Qian, Guojun Yin, Lu Sheng, Zixuan Chen, Jing Shao

As realistic facial manipulation technologies have achieved remarkable progress, social concerns about potential malicious abuse of these technologies bring out an emerging research topic of face forgery detection.

You Impress Me: Dialogue Generation via Mutual Persona Perception

1 code implementation ACL 2020 Qian Liu, Yihong Chen, Bei Chen, Jian-Guang Lou, Zixuan Chen, Bin Zhou, Dongmei Zhang

Despite the continuing efforts to improve the engagingness and consistency of chit-chat dialogue systems, the majority of current work simply focus on mimicking human-like responses, leaving understudied the aspects of modeling understanding between interlocutors.

Dialogue Generation

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