[image 04402] [CFP] PBDL 2021 : 3rd ICCV Workshop on Physics Based Vision meets Deep Learning

[iwaguchi ＠ ait.kyushu-u.ac.jp]

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.