[image 04485] Re: [CFP] PBDL 2021 : 3rd ICCV Workshop on Physics Based Vision meets Deep Learning

Takafumi Iwaguchi iwaguchi @ ait.kyushu-u.ac.jp
2021年 10月 11日 (月) 10:22:40 JST


ImageMLの皆さま
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九州大学の岩口です。
本日開催されるPBDLワークショップはどなたでも登録なしで参加できるように
なりました。是非ご参加ください。

==========
PBDL 2021 : 3rd ICCV Workshop on Physics Based Vision meets Deep
Learning
https://pbdl-ws.github.io/pbdl2021/
Date: 11 Oct 2021, Monday
Time: 8pm-1am (GMT+9 Tokyo)

Join Zoom Meeting via:
https://uva-live.zoom.us/j/87312056611
Meeting ID: 873 1205 6611

2021-07-26 15:46 に iwaguchi @ ait.kyushu-u.ac.jp さんは書きました:
> ImageMLの皆さま
> (重複してお受け取りの場合はご容赦ください。)
> 
> 九州大学の岩口です。
> Shaodi You先生、川崎先生、川上先生からの依頼で、ICCVワークショップのCFPを
> お送りします。
> 宜しくお願い致します。
> 
> ==========
> PBDL 2021 : 3rd ICCV Workshop on Physics Based Vision meets Deep 
> Learning
> https://pbdl-ws.github.io/pbdl2021/
> 
> • Workshop Dates: Oct 11, 2021, Virtual
> • Submission Deadline: Aug 2, 2021
> • Notification Due: Aug 23, 2021
> 
> ==========
> Call For Papers
> Following the success of 2nd ICCV Workshop on Physics Based Vision 
> Meets
> Deep Learning (PBDL2019). We propose the 3rd workshop using the same 
> title
> and topics with ICCV 2021. The goal is to encourage the interplay 
> between
> physics based vision and deep learning. Physics based vision aims to 
> invert
>  the processes to recover the scene properties, such as shape, 
> reflectance,
>  light distribution, medium properties, etc., from images. In recent 
> years,
>  deep learning shows promising improvement for various vision tasks. 
> When
> physics based vision meets deep learning, there must be mutual 
> benefits.
> 
> We welcome submissions of new methods in the classic physics based 
> vision
> problems, but preference will be given to novel insights inspired by
> utilizing deep learning techniques. Relevant topics include but are not
> limited to
> 
> Deep learning +
> • Photometric 3D reconstruction
> • Radiometric modeling/calibration of cameras
> • Color constancy
> • Illumination analysis and estimation
> • Reflectance modeling, fitting, and analysis
> • Forward/inverse renderings
> • Material recognition and classification
> • Transparency and multi-layer imaging
> • Reflection removal
> • Intrinsic image decomposition
> • Light field imaging
> • Multispectral/hyperspectral capture, modeling and analysis
> • Vision in bad weather (dehaze, derain, etc.)
> • Structured light techniques (sensors, BRDF measurement and analysis)
> • TOF sensors and its applications
> 
> Paper submission is through CMT:
> https://cmt3.research.microsoft.com/pbdl2021
> 
> The format for paper submission is the same as the ICCV 2021 submission
> format. Papers that violates the anonymity, do not use the ICCV 
> submission
> template or have more than 8 pages (excluding references) will be 
> rejected
> without review. The accepted papers will appear in the proceedings of 
> ICCV
> 2021 workshops. In submitting a manuscript to this workshop, the 
> authors
> acknowledge that no paper substantially similar in content has been
> submitted to another workshop or conference during the review period.

---
Takafumi Iwaguchi, PhD.
Assistant Professor
Faculty of Information Science and Electrical Engineering
Kyushu University
<iwaguchi @ ait.kyushu-u.ac.jp>


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