[image 03996] CFP: ACCV 2020 (Nov. 30 - Dec 4, 2020 Virtual from Kyoto)

[Ryo Yonetani]

image-MLの皆様、

（本内容を重複して受け取られた場合はご容赦ください）

Asian Conference on Computer Vision (ACCV2020) 広報チェアの米谷です。
ACCV2020は2020年11/30-12/4にオンライン開催されることになりました。
皆様からの多数のご投稿をお待ちしております。

CALL FOR PAPERS
Asian Conference on Computer Vision (ACCV 2020),
Virtual from Kyoto, Nov. 30 - Dec. 4, 2020
URL: http://accv2020.kyoto/
Email: accv2020-pcs ＠ googlegroups.com

Important Dates:
================
Paper submission deadline: Jul. 8, 2020
Supplementary material deadline: Jul. 13, 2020
Notification of acceptance: Sep. 18, 2020
Camera-ready paper deadline: Oct. 9, 2020
Main conference: Nov. 30 - Dec. 2, 2020
Workshops:Dec. 3 - 4, 2020

ACCV is a leading biennial international conference mainly sponsored
by Asian Federation of Computer Vision. This highly successful series
provides a premier forum for researchers, developers, and
practitioners to present and discuss new problems, solutions, and
technologies in computer vision and related areas.

Due to the COVID-19 pandemic, ACCV2020 will be held as a completely
online conference on the planned dates, Nov 30th to Dec 4th, 2020. The
organizing committee is committed to taking this opportunity to make
ACCV2020 a widely visible open conference. Your contributions and
participation will be key to its success!

ACCV 2020 solicits high-quality original research in all aspects of
computer vision for publication in its main conference and co-located
Workshops. The conference proceedings will be published by Springer in
the Lecture Notes in Computer Science (LNCS) series.

Topics include (but are not limited to):

* 3D Computer Vision
* Applications of Computer Vision, Vision for X
* Attention
* Big Data, Large Scale Methods
* Biomedical Image Analysis
* Biometrics
* Computational Photography, Sensing, and Display
* Datasets and Performance Analysis
* Deep learning for computer vision
* Document image analysis
* Face, Pose, Action, and Gesture
* Illumination and Reflectance Modeling
* Low-level Vision, Image Processing
* Motion and Tracking
* Optimization Methods
* Physics-based Vision and Shape from X
* Recognition: Feature Detection, Indexing, Matching, and Shape Representation
* RGBD and Depth Image Processing
* Robot Vision
* Segmentation and Grouping
* Statistical Methods and Learning
* Video Analysis and Event Recognition

General Chairs:
Ko Nishino (Kyoto Univ.), Long Quan (HUST), Hiromi Tanaka (Ritsumeikan Univ.)

Program Chairs:
Hiroshi Ishikawa (Waseda Univ.), Cheng-Lin Liu (NLPR),
Jianbo Shi (U. Pennsylvania), Tomas Pajdla (CTU)

Local Chairs:
Shohei Nobuhara (Kyoto Univ.), Yasushi Makihara (Osaka Univ.)