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<p class="MsoNormal"><span lang="EN-US">********************************<br>
<br>
Call for Papers<br>
<br>
FOCUS: FOundation models Creators meet USers<br>
<br>
International Workshop at ECCV 2024<br>
</span><a href="https://focus-workshop.github.io/"><span lang="EN-US">https://focus-workshop.github.io/</span></a><span lang="EN-US"><br>
<br>
********************************<br>
<br>
<br>
=== Submission Deadline: July 15, 2024 ====<br>
<br>
(11:59 p.m. CET)<br>
<br>
Apologies for multiple posting<br>
<br>
Please distribute this call to interested parties<br>
<br>
<br>
<br>
AIMS AND SCOPE<br>
===============<br>
<br>
</span><span lang="EN-US" style="font-family:"Arial",sans-serif">Over the last few years, the field of Artificial Intelligence has witnessed significant growth, largely fueled by the development of large-scale machine learning models. The foundational models
are characterized by extensive training on diverse datasets that encompass various input modalities (e.g. images, text, audio, 3D data), showing excellent flexibility and effectiveness across a wide range of standard NLP and Computer Vision tasks. Such general-purpose
solutions often reveal potentials that go beyond what their creators originally envisioned, motivating users to adopt these models for a broad spectrum of applications. </span><span lang="EN-US"><br>
<br>
<br>
</span><span lang="EN-US" style="font-family:"Arial",sans-serif">Nevertheless, the knowledge embedded in these models may not be enough when the final goal goes beyond perception benchmarks. These considerations spark important questions that can only be answered
with a collaborative dialogue between researchers developing these models (creators) and those employing them in downstream tasks (users). Each group brings a unique perspective that will be crucial in shaping the future of this technology. </span><span lang="EN-US"><br>
<br>
</span><span lang="EN-US" style="font-family:"Arial",sans-serif">The goal of this workshop is to identify and discuss strategies to assess both positive and negative (possibly unexpected) behaviors in the development and use of foundation models.</span><span lang="EN-US"><br>
</span><span lang="EN-US" style="font-family:"Arial",sans-serif">Particular attention will be given to applications that diverge significantly from the scenarios encountered during the training phase of foundational models. These include application-specific
visual understanding, uncertainty evaluation, goal-conditioned reasoning, human habits learning, task and motion planning, scene navigation, vision-based manipulation, etc. </span><span lang="EN-US"><br>
</span><span lang="EN-US" style="font-family:"Arial",sans-serif">Our purpose is to foster an open discussion between foundation model creators and users, targeting the analysis of the most pressing <strong><span style="font-family:"Arial",sans-serif">open questions</span></strong> for
the two communities and fostering new fruitful collaborations.</span><span lang="EN-US"><br>
<br>
<br>
TOPICS<br>
=======<br>
<br>
The workshop calls for submissions addressing, but not limited to, the<br>
following topics:<br>
<br>
- New vision-and-language applications<br>
- Supervised vs unsupervised based foundation model and downstream tasks<br>
- Zero-shot, Few-shot, continual and life-long learning of foundation model<br>
- Open set, out-of-distribution detection and uncertainty estimation<br>
- Perceptual reasoning and decision making: alignment with human intents and modeling<br>
- Prompt and Visual instruction tuning<br>
- Novel evaluation schemes and benchmarks<br>
- Task-specific vs general-purpose models<br>
- Robustness and generalization<br>
- Interpretability and explainability<br>
- Ethics and bias in prompting<br>
<br>
<br>
IMPORTANT DATES<br>
=================<br>
<br>
- Paper Submission Deadline: July 15th, 2024<br>
- Decision to Authors: July 31th, 2024<br>
- Camera ready papers due: August 15th, 2024<br>
<br>
<br>
SUBMISSION GUIDELINES<br>
======================<br>
<br>
Papers should be submitted at:<br>
</span><a href="https://cmt3.research.microsoft.com/FOCUS2024"><span lang="EN-US">https://cmt3.research.microsoft.com/FOCUS2024</span></a><span lang="EN-US"> <br>
<br>
At the time of submission, authors must indicate the type of the paper:<br>
<br>
- Full papers: must present original research, not published elsewhere, and follow the ECCV main conference policies and format with a maximum length of 14 pages (extra pages with references only are allowed). Accepted full papers will be included in the
ECCV 2024 Workshop proceedings. Supplemental materials are not allowed. <br>
<br>
- Short papers: previously or concomitantly published works that could foster the workshop objectives. Short-papers will have a maximum length of 4 pages (extra pages with references only are allowed), they will be presented without inclusion in the ECCV
2024 Workshop proceedings. Supplemental materials are not allowed. <br>
<br>
</span><span lang="EN-US" style="font-family:"Arial",sans-serif">The review process is double-blind and there is no rebuttal. </span><span lang="EN-US"><br>
<br>
<br>
<br>
</span>SPEAKERS<br>
======================<br>
<br>
<span style="font-family:"Arial",sans-serif">- Kira Zsolt, Professor, Georgia Tech</span><br>
<span style="font-family:"Arial",sans-serif">- Ishan Misra, Director, Facebook AI Research</span><br>
<span style="font-family:"Arial",sans-serif">- Hilde Kuehne, University of Bonn</span><br>
<br>
<br>
<br>
ORGANIZING COMMITTEE<br>
======================<br>
<br>
<span style="font-family:"Arial",sans-serif">- Antonio Alliegro, Politecnico di Torino</span><br>
<span style="font-family:"Arial",sans-serif">- Francesca Pistilli, Politecnico di Torino</span><br>
<span style="font-family:"Arial",sans-serif">- Songyou Peng, ETH Zurich</span><br>
<span style="font-family:"Arial",sans-serif">- Biplab Banerjee, IIT Bombay</span><br>
<span style="font-family:"Arial",sans-serif">- Gabriela Csurka, Naver Labs Europe</span><br>
<span style="font-family:"Arial",sans-serif">- Giuseppe Averta, Politecnico di Torino</span><span style="font-size:12.0pt;mso-ligatures:none;mso-fareast-language:IT"><o:p></o:p></span></p>
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