ICPR2020 Workshop on Multi-Modal Deep Learning: Challenges and Applications (MMDLCA 2020)

FIRST CALL FOR PAPERS
International Workshop on Multi-Modal Deep Learning: Challenges and Applications (MMDLCA 2020), Milan, Italy, September 18, 2020 (https://medical-and-multimedia-lab.github.io/MMDLCA2020/)
In conjunction with the 25th International Conference on Pattern Recognition (ICPR 2020), Milan, Italy, September 13-18, 2020 (https://www.micc.unifi.it/icpr2020/)
INFORMATION ON MMDLCA
Deep learning is now recognized as one of the key software engines that drives the new industrial revolution. The majority of current deep learning research efforts have been dedicated to single-modal data processing. Pronounced manifestations are deep learning based visual recognition and speech recognition. Although significant progress made, single-modal data is often insufficient to derive accurate and robust deep models in many applications. Our digital world is by nature multi-modal, that combines different modalities of data such as text, audio, images, animations, videos and interactive content. Multi-modal is the most popular form for information representation and delivery. For example, posts for hot social events are typically composed of textual descriptions, images and videos. For medical diagnosis, the joint use of medical imaging and textual reports is also essential. Multi-modal data is common for human to make accurate perceptions and decisions. Multi-modal deep learning that is capable of learning from information presented in multiple modalities and consequently making predictions based on multi-modal input is much in demand.
This workshop calls for scientific works that illustrate the most recent progress on multi-modal deep learning. In particular, multi-modal data capture, integration, modelling, understanding and analysis, and how to leverage them to derive accurate and robust AI models in many applications. It is a timely topic following the rapid development of deep learning technologies and their remarkable applications to many fields. It will serve as a forum to bring together active researchers and practitioners to share their recent advances in this exciting area. In particular, we solicit original and high-quality contributions in: (1) presenting state-of-the-art theories and novel application scenarios related to multi-modal deep learning; (2) surveying the recent progress in this area; and (3) developing benchmark datasets and evaluations. We welcome contributions coming from various communities (i.e., visual computing, machine learning, multimedia analysis, distributed and cloud computing, etc.) to submit their novel results.
TOPICS
The list of topics includes, but not limited to:
Multi-modal intelligent data acquisition and management
Multi-modal benchmark datasets and evaluations
Multi-modal representation learning and applications
Multi-modal data driven visual analysis and understanding
Multi-modal object detection, classification, recognition and segmentation
Multi-modal information tracking, retrieval and identification
Multi-modal social event analysis
Multi-modal medical diagnosis
Multi-modal machine learning from incomplete data
Deep neural network architectures for multi-modal data processing
Multi-modal big data analytics
Emerging multi-modal deep learning applications
SUBMISSION GUIDELINES 
Submissions must be formatted in accordance with the Springer's Computer Science Proceedings guidelines (https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines). Two types of contribution will be considered: 
Full papers (10-12 pages, including references)
Short papers (6-8 pages, including references)
Accepted manuscripts will be included in the ICPR 2020 Workshop Proceedings Springer volume. Once accepted, at least one author is expected to attend the event and orally present the paper. The submission platform will be available soon.
IMPORTANT DATES
Workshop submission deadline: June 15, 2020
Workshop author notification: July 15, 2020
Camera-ready submission: July 30, 2020
Finalized workshop program: August 15, 2020
Workshop day: September 18, 2020
CONTACTS
For any inquiry you may have, please send an email to: 
Zhineng Chen at zhineng.chen@ia.ac.cn,
Xirong Li at xirong@ruc.edu.cn,
Ioannis (Yiannis) Kompatsiaris ikom@iti.gr

ECCV 2020 Workshop – Beyond mAP: Reassessing the Evaluation of Object Detectors – Call for Papers

Call for Papers: ECCV 2020 Workshop – Beyond mAP: Reassessing the Evaluation of Object Detectors

Workshop link
Workshop summary

This workshop assesses current evaluation procedures for object detection, highlights their shortcomings and opens discussion for possible improvements.

Through a focus on evaluation using challenges, the object detection community has been able to quickly identify which methods are effective by examining performance metrics. However, as this technological boom progresses, it is important to assess whether our evaluation metrics and procedures adequately align with how object detection will be used in practical applications. Quantitative results should be easily reconciled with a detector’s performance in applied tasks. This workshop provides a forum to discuss these ideas and evaluate whether current standards meet the needs of the object detection community.

Call for Papers

We invite authors to contribute papers to the workshop. Topics of interest comprise, but are not limited to:

  • New evaluation measures/metrics for object detection
  • New evaluation/visualization tools to analyze object detection systems
  • New evaluation procedures for better understanding object detection performance
  • Examinations of current evaluation procedures
  • New datasets designed to examine specific challenges in object detection
  • New detection methods that provide contributions/insights unrewarded by current evaluation procedures (e.g. improved detector calibration, probabilistic object detection, etc.)
Author Instructions
  • Submissions must follow the ECCV format and be up to 4 pages in length including references
  • It is accepted if this is an abbreviated version of a larger paper published elsewhere if properly referenced
  • Submit your paper through CMT (link)
  • Accepted papers will be presented at a poster session
Note on PrOD Competition
You may also be accepted to present your work at our conference if you perform well on the 3rd Probabilistic Object Detection (PrOD) Challenge.
Details can be found at the workshop website as well as the main competition page below.

If you have any questions don't hesitate to contact.
Best regards,

Dr David Hall

Research Fellow

Robotic Vision Benchmarking and Evaluation Project

Australian Centre for Robotic Vision

Queensland University of Technology

e-mail: d20.hall@qut.edu.au

Phone: +61 7 31380656

ORCiD: 0000-0002-5520-0128

Website: https://sites.google.com/view/davidhallcv/home

Call for Papers-ECCV Workshop on Imbalance Problems in Computer Vision (IPCV)

Hi,


We are organizing a workshop on imbalance problems in computer vision in ECCV 2020. Details are provided below


**ECCV Workshop on Imbalance Problems in Computer Vision (IPCV)**

28 August 2020, Glasgow

https://sites.google.com/view/ipcv2020/

**Dates:**

Paper submission: 7 July 2020

Notification: 28 July 2020

Camera ready: 7 August 2020

Workshop: 28 August 2020

**Workshop Theme and Scope**

Performance of learning-based methods is adversely affected by imbalance problems at various levels, including the input, intermediate or mid-level stages of the processing or the objectives to be optimized in a multi-task setting. Currently, researchers tend to address these challenges in their particular context with problem-specific solutions and with limited awareness of the solutions proposed for similar challenges in other computer vision problems.

Imbalance problems can arise in  almost all computer vision problems and therefore, the workshop is highly relevant and interesting for a broad community. A recent, comprehensive review paper on imbalance problems in object detection (IEEE TPAMI, 2020; preprint: https://arxiv.org/abs/1909.00169)  cites over 200 papers which were written by 655 unique authors. We interpret these numbers (which are specific to just one computer vision task, namely, object detection) as strong indicators of interest in imbalance problems.

We invite contributions for (i) the dissemination of approaches developed in individual problems, as well as (ii) discussing commonalities between these approaches for developing better and more general solutions for addressing imbalance problems in computer vision.

**Paper Submission**

Paper template and length: Please follow ECCV2020 format and guidelines.

Submission link: https://openreview.net/group?id=thecvf.com/ECCV/2020/Workshop/IPCV

**Proceedings:** 

Accepted papers will be included in ECCV2020 Workshop Proceedings.

**Presentation Information**

All accepted papers will have a spotlight presentation followed by a poster session.

**Organizers**

Sinan Kalkan, University of Cambridge; Middle East Technical University

Emre Akbas, Middle East Technical University

Nuno Vasconcelos, University of  California San Diego

Baris Can Cam, Middle East Technical University

Kemal Oksuz, Middle East Technical University

Baris

CVPR 2020 New Trends in Image Restoration and Enhancement (NTIRE) workshop [Deadline extended March 22]


CALL FOR PAPERS  & CALL FOR PARTICIPANTS IN 9 CHALLENGES
NTIRE: 5th New Trends in Image Restoration and Enhancement workshop and challenges on real world super-resolution, extreme SR,
denoising, demoireing, deblurring, spectral reconstruction, quality mapping, nonhomogeneous dehazing
In conjunction with CVPR 2020, June 15, Seattle, USA.
TOPICS
● Image/video inpainting
● Image/video deblurring
● Image/video denoising
● Image/video upsampling and super-resolution
● Image/video filtering
● Image/video de-hazing, de-raining, de-snowing, etc.
● Demosaicing
● Image/video compression
● Removal of artifacts, shadows, glare and reflections, etc.
● Image/video enhancement: brightening, color adjustment, sharpening, etc.
● Style transfer
● Hyperspectral imaging
● Underwater imaging
● Methods robust to changing weather conditions / adverse outdoor conditions
● Image/video restoration, enhancement, manipulation on constrained settings
● Image/video processing on mobile devices
● Visual domain translation
● Multimodal translation
● Perceptual enhancement
● Perceptual manipulation
● Depth estimation
● Image/video generation and hallucination
● Image/video quality assessment
● Image/video semantic segmentation, depth estimation
● Studies and applications of the above.

SUBMISSION
A paper submission has to be in English, in pdf format, and at most 8 pages (excluding references) in CVPR style.
The review process is double blind.
Accepted and presented papers will be published after the conference in the CVPR 2020 Workshops Proceedings.

Author Kit: http://cvpr2020.thecvf.com/sites/default/files/2019-09/cvpr2020AuthorKit.zip
 

WORKSHOP DATES
Regular Papers Submission Deadline: March 22, 2020 (EXTENDED!)
● Challenge Papers Submission Deadline: April 04, 2020

IMAGE CHALLENGES (ongoing!)
  1. Perceptual Extreme Super-Resolution (x16)
  2. Real-World Super-Resolution
  3. Real Denoising (rawRGB and sRGB)
  4. Deblurring  (on desktop and on smartphone)
  5. Demoireing (single image and burst)
  6. Spectral Reconstruction from RGB
  7. Nonhomogeneous Dehazing

VIDEO CHALLENGES (ongoing!)
  1. Quality Mapping (supervised and weakly supervised)
  2. Deblurring
To learn more about the challenges, to participate in the challenges, and to access the data everybody is invited to check the NTIRE webpage:
http://www.vision.ee.ethz.ch/ntire20/
CHALLENGES DATES

● Release of train data: January 10, 2020
Competitions end: March 23, 2020

ORGANIZERS

● Radu Timofte, ETH Zurich, Switzerland
● Martin Danelljan, ETH Zurich, Switzerland
● Shuhang Gu, ETH Zurich, Switzerland & University of Sydney, Australia
● Kai Zhang, ETH Zurich, Switzerland
● Lei Zhang, The Hong Kong Polytechnic University
● Ming-Hsuan Yang, University of California at Merced, US
● Luc Van Gool, ETH Zurich, Switzerland 
and KU Leuven, Belgium

● Cosmin Ancuti, UPT, Romania
● Codruta O. Ancuti, University Politehnica Timisoara, Romania
● Kyoung Mu Lee, Seoul National University, Korea
● Michael S. Brown, York University, Canada
● Eli Shechtman, Adobe Research
● Zhiwu Huang, ETH Zurich, Switzerland
● Seungjun Nah, Seoul National University, Korea
● Abdelrahman Kamel Siddek Abdelhamed, York University, Canada
● Mahmoud Afifi, York University, Canada
● Boaz Arad, Voyage 81, Israel
● Shanxin Yuan, Huawei Noah's Ark Lab, UK
● Gregory Slabaugh, Huawei Noah's Ark Lab, UK

SPEAKERS (TBA)
SPONSORS (TBU)
CVL / ETH Zurich
Huawei
Oppo
Disney Research
MediaTek
Voyage81

CVPR 2020 New Trends in Image Restoration and Enhancement (NTIRE) workshop [Deadline extended March 22]

NTIRE: 5th New Trends in Image Restoration and Enhancement workshop and challenges on real world super-resolution, extreme SR,
denoising, demoireing, deblurring, spectral reconstruction, quality mapping, nonhomogeneous dehazing
In conjunction with CVPR 2020, June 15, Seattle, USA.
TOPICS
● Image/video inpainting
● Image/video deblurring
● Image/video denoising
● Image/video upsampling and super-resolution
● Image/video filtering
● Image/video de-hazing, de-raining, de-snowing, etc.
● Demosaicing
● Image/video compression
● Removal of artifacts, shadows, glare and reflections, etc.
● Image/video enhancement: brightening, color adjustment, sharpening, etc.
● Style transfer
● Hyperspectral imaging
● Underwater imaging
● Methods robust to changing weather conditions / adverse outdoor conditions
● Image/video restoration, enhancement, manipulation on constrained settings
● Image/video processing on mobile devices
● Visual domain translation
● Multimodal translation
● Perceptual enhancement
● Perceptual manipulation
● Depth estimation
● Image/video generation and hallucination
● Image/video quality assessment
● Image/video semantic segmentation, depth estimation
● Studies and applications of the above.

SUBMISSION
A paper submission has to be in English, in pdf format, and at most 8 pages (excluding references) in CVPR style.
The review process is double blind.
Accepted and presented papers will be published after the conference in the CVPR 2020 Workshops Proceedings.

Author Kit: http://cvpr2020.thecvf.com/sites/default/files/2019-09/cvpr2020AuthorKit.zip
 

WORKSHOP DATES
Regular Papers Submission Deadline: March 22, 2020 (EXTENDED!)
● Challenge Papers Submission Deadline: April 04, 2020

IMAGE CHALLENGES (ongoing!)
  1. Perceptual Extreme Super-Resolution (x16)
  2. Real-World Super-Resolution
  3. Real Denoising (rawRGB and sRGB)
  4. Deblurring  (on desktop and on smartphone)
  5. Demoireing (single image and burst)
  6. Spectral Reconstruction from RGB
  7. Nonhomogeneous Dehazing

VIDEO CHALLENGES (ongoing!)
  1. Quality Mapping (supervised and weakly supervised)
  2. Deblurring
To learn more about the challenges, to participate in the challenges, and to access the data everybody is invited to check the NTIRE webpage:
http://www.vision.ee.ethz.ch/ntire20/
CHALLENGES DATES

● Release of train data: January 10, 2020
Competitions end: March 23, 2020

ORGANIZERS

● Radu Timofte, ETH Zurich, Switzerland
● Martin Danelljan, ETH Zurich, Switzerland
● Shuhang Gu, ETH Zurich, Switzerland & University of Sydney, Australia
● Kai Zhang, ETH Zurich, Switzerland
● Lei Zhang, The Hong Kong Polytechnic University
● Ming-Hsuan Yang, University of California at Merced, US
● Luc Van Gool, ETH Zurich, Switzerland 
and KU Leuven, Belgium

● Cosmin Ancuti, UPT, Romania
● Codruta O. Ancuti, University Politehnica Timisoara, Romania
● Kyoung Mu Lee, Seoul National University, Korea
● Michael S. Brown, York University, Canada
● Eli Shechtman, Adobe Research
● Zhiwu Huang, ETH Zurich, Switzerland
● Seungjun Nah, Seoul National University, Korea
● Abdelrahman Kamel Siddek Abdelhamed, York University, Canada
● Mahmoud Afifi, York University, Canada
● Boaz Arad, Voyage 81, Israel
● Shanxin Yuan, Huawei Noah's Ark Lab, UK
● Gregory Slabaugh, Huawei Noah's Ark Lab, UK

SPEAKERS (TBA)
SPONSORS (TBU)
CVL / ETH Zurich
Huawei
Oppo
Disney Research
MediaTek
Voyage81
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