Learning to Denoise Raw Mobile UI Layouts for Improving Datasets at Scale-Reference-Cited by-同舟云学术

Learning to Denoise Raw Mobile UI Layouts for Improving Datasets at Scale

Published:2022-04-27 Issue: Volume: Page:
ISSN:
Container-title:CHI Conference on Human Factors in Computing Systems
language:
Short-container-title:

Author:

Li Gang¹,Baechler Gilles²,Tragut Manuel³,Li Yang¹

Affiliation:

1. Google Research, United States

2. Google Research, Switzerland

3. Google Research, Google, Switzerland

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3491102.3502042

Reference33 articles.

1. Chongyang Bai Xiaoxue Zang Ying Xu Srinivas Sunkara Abhinav Rastogi Jindong Chen and Blaise Aguera y Arcas. 2021. UIBert: Learning Generic Multimodal Representations for UI Understanding. arxiv:2107.13731 [cs.CV] Chongyang Bai Xiaoxue Zang Ying Xu Srinivas Sunkara Abhinav Rastogi Jindong Chen and Blaise Aguera y Arcas. 2021. UIBert: Learning Generic Multimodal Representations for UI Understanding. arxiv:2107.13731 [cs.CV]

2. Andrea Burns , Deniz Arsan , Sanjna Agrawal , Ranjitha Kumar , Kate Saenko , and Bryan A Plummer . 2021. Mobile App Tasks with Iterative Feedback (MoTIF): Addressing Task Feasibility in Interactive Visual Environments. (April 2021 ). arxiv:2104.08560 [cs.CL] Andrea Burns, Deniz Arsan, Sanjna Agrawal, Ranjitha Kumar, Kate Saenko, and Bryan A Plummer. 2021. Mobile App Tasks with Iterative Feedback (MoTIF): Addressing Task Feasibility in Interactive Visual Environments. (April 2021). arxiv:2104.08560 [cs.CL]

3. End-to-End Object Detection with Transformers

4. Revolt

5. Object detection for graphical user interface: old fashioned or deep learning or a combination?

Cited by 16 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Understanding mobile GUI: From pixel-words to screen-sentences;Neurocomputing;2024-10

2. UI semantic component group detection: Grouping UI elements with similar semantics in mobile graphical user interface;Displays;2024-07

3. On Improving the Qualitative Features of the User Interface of Mobile Applications Using Machine Learning Methods;2024 47th MIPRO ICT and Electronics Convention (MIPRO);2024-05-20

4. Graph4GUI: Graph Neural Networks for Representing Graphical User Interfaces;Proceedings of the CHI Conference on Human Factors in Computing Systems;2024-05-11

5. MUD: Towards a Large-Scale and Noise-Filtered UI Dataset for Modern Style UI Modeling;Proceedings of the CHI Conference on Human Factors in Computing Systems;2024-05-11