Call for papers
January 31st, 2022 
Daniela Lopez de Luise HEAd'22: Call for Papers
8th International Conference on Higher Education Advances
June 14 – 17, 2022. Valencia, Spain (hybrid conference)
http://www.headconf.org
Scope
We are pleased to announce the Eighth International Conference on Higher Education Advances (HEAd’22), as a hybrid conference (in-person and virtual conference, simultaneously). Every year, HEAd brings together around 250 participants from more than 50 countries to exchange ideas, experiences and research results related to the preparation of students, teaching/learning methodologies and the organization of educational systems.
The HEAd'22 conference will be held on June 14-17, 2022 on the Faculty of Business Administration and Management of the Universitat Politècnica de València (UPV), which has been recently ranked as the best technical university in Spain by the Academic Ranking of World Universities (ARWU) 2021.
Topics of interest
The program committee encourages the submission of articles that communicate applied and empirical findings of interest to higher education professionals.
Topics of interest include, but are not limited to, the following topic areas:
- Innovative materials and new tools for teaching
- Educational technology (e.g., virtual labs, e-learning)
- Evaluation and assessment of student learning
- Emerging technologies in learning (e.g., MOOC, OER, gamification)
- Scientific and research education
- Experiences outside the classroom (e.g., practicums, mobility)
- New teaching/learning theories and models
- Globalization in education and education reforms
- Education economics
- Teaching and learning experiences
- Entrepreneurship and learning for employment
- Education accreditation, quality and assessment
- Competency-based learning and skill assessment
Important Dates
Submission deadline: February 4, 2022
Acceptance notification: April 6, 2022
Camera ready due: April 25, 2022
Conference dates: June 14-17, 2022
Publications
All accepted papers will appear in the conference proceedings with a DOI and ISBN number. They will be published in open access by UPV Press and submitted to be indexed in major international bibliographic databases. Previous editions are indexed in Scopus and the Thomson-Reuters Conference Proceedings Citation Index – Web of Science Core Collection (former ISI Proceedings).
Awards
The Program Committee will select the winners for the Best Paper and Best Student Paper awards. To be eligible for the best student paper award, the presenting author of the paper must be a full-time student.
Submission guidelines
Authors from all over the world are invited to submit original and unpublished papers, which are not under review in any other conference or journal. All papers will be peer reviewed by the program committee based on their originality, significance, methodological soundness, and clarity of exposition.
Submitted papers must be written in English and should be in PDF format. They must follow the instructions in the template file, available in Microsoft Word format at:
http://www.headconf.org/template.docx
Paper length must be between 4 and 8 pages, incorporating all text, references, figures and tables. Submissions imply the willingness of at least one author to register, attend the conference, and present the paper.
HEAd'22 is using the OCS platform of UPV Press to manage the submissions. This platform provides you with a submissions homepage where you can register your paper submission and make appropriate changes. The submission website is:
http://www.headconf.org/submission-instructions/
The organizing committee looks forward to welcoming you all to a fruitful conference with open discussions and important networking to promote high quality education.
Call For Participation: SHREC 2022 Track – Sketch-Based 3D Shape Retrieval in the Wild
January 31st, 2022 Daniela Lopez de Luise * SHREC 2022 Track: Sketch-Based 3D Shape Retrieval in the Wild
* Website:
https://sites.google.com/site/firmamentqj/sbsrw
* Registration Deadline: January 22
* Organizers:
– Jie Qin, Nanjing University of Aeronautics and Astronautics, Nanjing, China
– Shuaihang Yuan, New York University, New York, USA
– Jiaxin Chen, Beihang University, Beijing, China
– Boulbaba Ben Amor – IMT Nord Europe, France & Inception Institute of Artificial Intelligence, UAE
– Yi Fang, NYU Abu Dhabi, UAE and NYU Tandon, USA
============================ Objective =================================
The objective of this track is to evaluate the performance of different sketch-based 3D shape retrieval algorithms based on a 2D free-hand sketch dataset and a 3D shape dataset in a more realistic and challenging setting.
============================ Introduction ================================
Sketch-based 3D shape retrieval (SBSR) [1-3] has drawn a significant amount of attention, owing to the succinctness of free-hand sketches and the increasing demands from real applications. It is an intuitive yet challenging task due to the large discrepancy between the 2D and 3D modalities.
To foster the research on this important problem, several tracks focusing on related tasks have been held in the past SHREC challenges, such as [4-7]. However, the datasets they adopted are not quite realistic, and thus cannot well simulate real application scenarios. To mimic the real-world scenario, the dataset is expected to meet the following requirements. First, there should exist a large domain gap between the two modalities, i.e., sketches and 3D shapes. However, current datasets unintentionally narrow this gap by using projection-based/multi-view representations for 3D shapes (i.e., a 3D shape is manually rendered into a set of 2D images). In this way, the large 2D-3D domain discrepancy is unnecessarily reduced to the 2D-2D one. Second, the data themselves from both modalities should be realistic, mimicking the real-world scenario. More specifically, we need a full variety of sketches per category as real users possess various drawing skills. As for 3D shapes, we need to frame 3D models with real-world settings more than create them artificially. However, human sketches on existing datasets tend to be semi-photorealistic drawn by experts and the number of sketches per category is quite limited; in the meantime, most current 3D datasets used in SBSR are composed of CAD models, losing certain details compared to the models scanned from real objects.
To circumvent the above limitations, this track proposes a more realistic and challenging setting for SBSR. On the one hand, we adopt highly abstract 2D sketches drawn by amateurs, and at the same time, bypass the projection-based representations for 3D shapes by directly adopting and representing 3D point cloud data. On the other hand, we adopt a full variety of free-hand sketches with various samples per category, as well as a collection of realistic point cloud data framed from indoor objects. Therefore, we name this track ‘sketch-based 3D shape retrieval in the wild’ (SBSRW). As stated above, the term ‘in the wild’ is reflected in two perspectives: 1) The domain gap between the two modalities is realistic as we adopt sketches of high abstraction levels and 3D point cloud data. 2) The data themselves mimic the real-world setting as we adopt a full variety of sketches (3,000 per category) and 3D point clouds captured from real objects.
======================= Tasks ===========================
We proposed two tasks to evaluate the performance of different SBSR algorithms, i.e., sketch-based 3D CAD model (point cloud data) retrieval and sketch-based realistic scanned model (point cloud data) retrieval.
For the first task, we select around 2,500 3D CAD models from 47 classes on ModelNet40/ShapeNet and 3,000 sketches from each corresponding category (141,000 sketch samples in total) on QuickDraw. We randomly select 2,500 sketches from each class for training, and the remaining 500 sketches per class are used for testing/query. All the 3D point clouds as a whole are utilized as the target/gallery dataset to evaluate the retrieval performance. Participants are asked to submit the results on the test datasets.
For the second task, we select 2,000 realistic 3D models from 11 classes on ScanObjectNN and 3,000 sketches per class (33,000 sketch samples in total) from QuickDraw. Similar to the first task, we randomly select 2,500 sketches from each class for training, and the remaining 500 sketches per class are used for testing/query. All the 3D point clouds as a whole are utilized as the target/gallery dataset to evaluate the retrieval performance. Participants are asked to submit the results on the test datasets.
======================= Evaluation Method ===========================
For a comprehensive evaluation of different algorithms, we employ the following widely-adopted performance metrics in SBSR, including nearest neighbor (NN), first tier (FT), second tier (ST), E-measure (E), discounted cumulated gain (DCG), mean average precision (mAP), and precision-recall (PR) curve. We will provide the source code to compute all the aforementioned metrics.
======================= Procedure ===========================
The following list is a step-by-step description of the activities:
- The participants register the track by sending an email to qinjiebuaa@gmail.com with 'SHREC 2022 – SBSRW Track Registration' as the title and indicating which task they are interested in.
- The organizers release the dataset via their website.
- The participants submit the distance matrices for the test sets, with one-page descriptions of their methods.
- Evaluation is automatically performed based on the submitted matrices, by computing all the performance metrics via the official source code.
- The organizers announce the results and the final rank list of all the participants.
- The track results are combined into a joint paper, which is subject to a two-stage peer review process. Accepted papers will be published in Computers & Graphics.
- The description of the track and the results will be presented at Eurographics 2022 Symposium on 3D Object Retrieval (1-2 September 2022).
======================= Schedule ===========================
- January 1: Call for participation.
- January 15: Release a few sample sketches and 3D models.
- January 22: Registration deadline.
- January 29: Release the training set for the first task.
- February 5: Release the training set for the second task.
- February 28: Submission deadline for the first task.
- March 4: Submission deadline for the second task.
- March 8: Release the final results for both tasks; jointly write the track report.
- March 15: Submission deadline for the joint paper for C&G review.
We look forward to your participation!
Best Regards,
Jie Qin
Professor
College of Computer Science and Technology
Nanjing University of Aeronautics and Astronautics (NUAA)
Nanjing, Jiangsu 211106, China
Winter School on Deep Learning: From Perceptrons to Transformers on Fridays and Saturdays during January 21 – March 12, 2022
January 31st, 2022 Daniela Lopez de Luise 
cfp-deep-winter-school-v4.pdfSLPAT 2022 (Organized by the ACL/ISCA SIG-SLPAT)
January 31st, 2022 Daniela Lopez de Luise Hello,
We are pleased to announce the first call for papers for the Ninth Workshop on Speech and Language Processing for Assistive Technologies (SLPAT) on May 27, 2022, co-located with ACL 2022 in Dublin: Ireland
This workshop will bring together researchers from areas such as natural language processing, speech signal processing, (special) education, rehabilitation sciences, computer science, HCI, communication, psychology, psycholinguistics, computer vision, and computer graphics with a common interest in making everyday life more accessible for people with physical, cognitive, sensory, emotional, or developmental disabilities as well as older adults. The workshop will provide an opportunity for researchers, domain experts, and users of assistive technology (AT) to share their findings, to discuss present and future challenges, and to explore possibilities for collaboration.
Possible topics include but are not limited to:
- Speech synthesis for physical, cognitive, or sensory impairments (talking devices in Augmentative and Alternative Communication (AAC), screen readers, audio description/audio subtitling using speech synthesis)
- Sign synthesis (sign language animation, synthetic videos)
- Speech recognition (AAC, respeaking for live subtitling, fully automatic subtitling)
- Sign recognition (AT, natural user interfaces for sign language resources, computer-augmented corpus annotation, sign language assessment)
- Speech and language technologies for daily assisted living and Ambient/Active Assisted Living (AAL)
- Translation to and from speech, text (including subtitles), pictographs, Braille, and sign language
- Novel modeling and machine learning approaches for AT
- Personalized voices for AAC based on limited data
- Biofeedback for therapy in neurological disorders
- Text generation for improved comprehension (e.g., sentence and text simplification)
- Silent speech: speech technology based on sensors without audio
- Nonverbal communication
- Multimodal user interfaces and dialogue systems adapted to AT
- Speech and language technologies for cognitive assistance applications
- Presentation of graphical information for people with visual impairments
- Speech and language technologies applied to typing interface applications
- Brain-computer interfaces for language processing applications
- Assessment of speech and language processing within the context of AT
- Web accessibility, media accessibility
- Deployment of speech and language technologies in the clinic or in the field, such as language analysis for diagnosis or intervention
- Linguistic resources; corpora and annotation schemes
- Automatic evaluation within the context of AT
- Reception studies with target user groups
- Ethical considerations and standards within the context of AT
- Crowdsourcing and Citizen Science efforts within the context of AT
Please contact the conference organizers at slpat2022-organizers@googlegroups.com with any questions.
Important dates (subject to change)
| February 28, 2022: | Deadline for papers |
| March 26, 2022: | Notification of acceptance |
| April 10, 2022: | Camera-ready paper due |
| May 27, 2022: | Workshop |