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"Connected to the people": Social Inclusion & Cohesion in Action through a Cultural Heritage Digital Tool

Proceedings of the ACM on Human-Computer Interaction 2023年第CSCW2期7卷 1-37页

作者： Nisi, Valentina Bala, Paulo Cesário, Vanessa James, Stuart Del Bue, Alessio Nunes, Nuno Jardim Instituto Superior Técnico U. Lisbon Lisbon Portugal Visual Geometry and Modelling Lab Pattern Analysis and Computer Vision Istituto Italiano di Tecnologia Genova Italy Pattern Analysis and Computer Vision Istituto Italiano di Tecnologia Genova Italy

Current cultural policies are evolving from social inclusion (removing barriers and promoting equality for participation in culture) to social cohesion (fostering solid bonds between groups despite their differences). Digital interventions can create spaces that promote social inclusion and cohesion. In this paper, we report on the design and evaluation of a cultural heritage and digital storytelling application supporting a participatory approach to culture and hosting society. We evaluate our intervention in three marginalized communities with different social-cultural contexts: migrant women in Barcelona, a community living in a priority neighbourhood in Paris and second and third-generation migrants in Lisbon. Through an analysis of their application use, our findings point at their needs and desires, highlighting how the app can support social inclusion as the first step towards cohesion, but that these are heterogeneous concepts susceptible to nuanced appropriations by the different communities. © 2023 ACM.

关键词： Digital devices

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A Benchmark and Evaluation of Non-Rigid Structure from Motion

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INTERNATIONAL JOURNAL OF COMPUTER VISION 2021年第4期129卷 882-899页

作者： Jensen, Sebastian Hoppe Nesgaard Doest, Mads Emil Brix Aanaes, Henrik Del Bue, Alessio DTU Compute Lyngby Denmark Ist Italiano Tecnol IIT Visual Geometry & Modelling VGM Lab Pattern Anal & Comp Vis PAVIS I-08028 Genoa Italy

Non-rigid structure from motion (nrsfm), is a long standing and central problem in computer vision and its solution is necessary for obtaining 3D information from multiple images when the scene is dynamic. A main issue regarding the further development of this important computer vision topic, is the lack of high quality data sets. We here address this issue by presenting a data set created for this purpose, which is made publicly available, and considerably larger than the previous state of the art. To validate the applicability of this data set, and provide an investigation into the state of the art of nrsfm, including potential directions forward, we here present a benchmark and a scrupulous evaluation using this data set. This benchmark evaluates 18 different methods with available code that reasonably spans the state of the art in sparse nrsfm. This new public data set and evaluation protocol will provide benchmark tools for further development in this challenging field.

关键词： Non-rigid structure from motion Dataset Evaluation Deformation modelling

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Writing with (Digital) Scissors: Designing a Text Editing Tool for Assisted Storytelling Using Crowd-Generated Content 15th

Writing with (Digital) Scissors: Designing a Text Editing To...

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15th International Conference on Interactive Digital Storytelling (ICIDS)

作者： Bala, Paulo James, Stuart Del Bue, Alessio Nisi, Valentina ITI LARSyS Lisbon Portugal Univ Lisbon IST Lisbon Portugal Ist Italiano Tecnol Visual Geometry & Modelling VGM Lab Genoa Italy Ist Italiano Tecnol Pattern Anal & Comp Vis PAVIS Genoa Italy

ISBN: (纸本)9783031222979;9783031222986

Digital Storytelling can exploit numerous technologies and sources of information to support the creation, refinement and enhancement of a narrative. Research on text editing tools has created novel interactions that support authors in different stages of the creative process, such as the inclusion of crowd-generated content for writing. While these interactions have the potential to change workflows, integration of these in a way that is useful and matches users' needs is unclear. In order to investigate the space of Assisted Storytelling, we designed and conducted a study to analyze how users write and edit a story about Cultural Heritage using an auxiliary source like Wikipedia. Through a diffractive analysis of stories, creative processes, and social and cultural contexts, we reflect and derive implications for design. These were applied to develop an AI-supported text editing tool using crowd-sourced content from Wikipedia and Wikidata.

关键词： Digital storytelling Text editing Artificial intelligence Crowd-sourced content Knowledge graphs

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Fill in the blank for fashion complementary outfit product Retrieval: VISUM summer school competition

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MACHINE VISION AND APPLICATIONS 2023年第1期34卷 1-15页

作者： Castro, Eduardo Ferreira, Pedro M. Rebelo, Ana Rio-Torto, Isabel Capozzi, Leonardo Ferreira, Mafalda Falcao Goncalves, Tiago Albuquerque, Tome Silva, Wilson Afonso, Carolina Gamelas Sousa, Ricardo Cimarelli, Claudio Daoudi, Nadia Moreira, Gabriel Yang, Hsiu-yu Hrga, Ingrid Ahmad, Javed Keswani, Monish Beco, Sofia INESC TEC Porto Portugal FARFETCH Porto Portugal Luxembourg Univ Interdisciplinary Ctr Secur Reliabil & Trust Kirchberg Luxembourg Carnegie Mellon Univ Language Technol Inst Pittsburgh PA USA Univ Stuttgart Stuttgart Germany Juraj Dobrila Univ Pula Pula Croatia Italian Inst Technol IIT Visual Geometry & Modelling VGM Lab Genoa Italy Univ Genoa Genoa Italy Indian Inst Technol Hyderabad India Univ Porto Porto Portugal

Every year, the VISion Understanding and Machine intelligence (VISUM) summer school runs a competition where participants can learn and share knowledge about Computer Vision and Machine Learning in a vibrant environment. 2021 VISUM's focused on applying those methodologies in fashion. Recently, there has been an increase of interest within the scientific community in applying computer vision methodologies to the fashion domain. That is highly motivated by fashion being one of the world's largest industries presenting a rapid development in e-commerce mainly since the COVID-19 pandemic. Computer Vision for Fashion enables a wide range of innovations, from personalized recommendations to outfit matching. The competition enabled students to apply the knowledge acquired in the summer school to a real-world problem. The ambition was to foster research and development in fashion outfit complementary product retrieval by leveraging vast visual and textual data with domain knowledge. For this, a new fashion outfit dataset (acquired and curated by FARFETCH) for research and benchmark purposes is introduced. Additionally, a competitive baseline with an original negative sampling process for triplet mining was implemented and served as a starting point for participants. The top 3 performing methods are described in this paper since they constitute the reference state-of-the-art for this particular problem. To our knowledge, this is the first challenge in fashion outfit complementary product retrieval. Moreover, this joint project between academia and industry brings several relevant contributions to disseminating science and technology, promoting economic and social development, and helping to connect early-career researchers to real-world industry challenges.

关键词： Image retrieval Summer school competition Computer vision Deep learning Fashion intelligence

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Mixing Modalities of 3D Sketching and Speech for Interactive Model Retrieval in Virtual Reality 21

Mixing Modalities of 3D Sketching and Speech for Interactive...

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ACM International Conference on Interactive Media Experiences (IMX)

作者： Giunchi, Daniele Sztrajman, Alejandro James, Stuart Steed, Anthony UCL Comp Sci London England Ist Italiano Tecnol Visual Geometry & Modelling VGM Lab Rome Italy UCL Dept Comp Sci London England

ISBN: (纸本)9781450383899

Sketch and speech are intuitive interaction methods that convey complementary information and have been independently used for 3D model retrieval in virtual environments. While sketch has been shown to be an efective retrieval method, not all collections are easily navigable using this modality alone. We design a new challenging database for sketch comprised of 3D chairs where each of the components (arms, legs, seat, back) are independently colored. To overcome this, we implement a multimodal interface for querying 3D model databases within a virtual environment. We base the sketch on the state-of-the-art for 3D Sketch Retrieval, and use a Wizard-of-Oz style experiment to process the voice input. In this way, we avoid the complexities of natural language processing which frequently requires fne-tuning to be robust. We conduct two user studies and show that hybrid search strategies emerge from the combination of interactions, fostering the advantages provided by both modalities.

关键词： Sketch Virtual Reality CNN HCI

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An integrated light management system with real-time light measurement and human perception

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LIGHTING RESEARCH & TECHNOLOGY 2021年第1期53卷 74-88页

作者： Tsesmelis, T. Hasan, I Cristani, M. Del Bue, A. Galasso, F. OSRAM Licht AG Dept Innovat & Innoventures Vis Lab Garching Germany Ist Italiano Tecnol Visual Geometry & Modelling Lab Genoa Italy Univ Verona Dept Comp Sci Vis Image Proc & Sound Lab Verona Italy Sapienza Univ Rome Dept Comp Sci Percept & Intelligence Lab Rome Italy

Illumination is important for well-being, productivity and safety across several environments, including offices, retail shops and industrial warehouses. Current techniques for setting up lighting require extensive and expert support and need to be repeated if the scene changes. Here we propose the first fully automated light management system which measures lighting in real-time, leveraging an RGBD sensor and a radiosity-based light propagation model. Thanks to the integration of light distribution and perception curves into the radiosity, we outperform a commercial software (Relux) on a newly introduced dataset. Furthermore, our proposed light management system is the first to estimate both the presence and the attention of the people in the environment, as well as their light perception. Our new light management system adapts lighting to the scene and human activity and it is capable of energy savings of up to 66%, as we experimentally quantify, without compromising the lighting quality.

关键词： Energy conservation

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LIGHTS: LIGHT SPECULARITY DATASET FOR SPECULAR DETECTION IN MULTI-VIEW

LIGHTS: LIGHT SPECULARITY DATASET FOR SPECULAR DETECTION IN ...

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IEEE International Conference on Image Processing (ICIP)

作者： Elkhouly, Mohamed Dahy Tsesmelis, Theodore Del Bue, Alessio James, Stuart Ist Italiano Tecnol IIT Visual Geometry & Modelling VGM Lab Genoa Italy Ist Italiano Tecnol IIT Pattern Anal & Comp Vis PAVIS Genoa Italy Univ Genoa Genoa Italy

ISBN: (纸本)9781665441155

Specular highlights are commonplace in images, however, methods for detecting them and removing the phenomenon are particularly challenging. A reason for this is the difficulty in creating a dataset for training or evaluation, as in the real world, we lack the necessary control over the environment. Therefore, we propose a novel physically-based rendered LIGHT Specularity (LIGHTS) Dataset for the evaluation of the specular highlight detection task. Our dataset consists of 18 high-quality architectural scenes, where each scene is rendered with multiple views. In total, the dataset contains 2;603 views with an average of 145 views per scene. Additionally, we propose a simple aggregation based method for specular highlight detection that outperforms prior work by 3:6% in two orders of magnitude less time on our dataset.

关键词： Specular-highlights Multi-view Dataset Face-based specular detection

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Fast re-OBJ: real-time object re-identification in rigid scenes

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MACHINE VISION AND APPLICATIONS 2022年第6期33卷 97-97页

作者： Bayraktar, Ertugrul Wang, Yiming DelBue, Alessio Yildiz Tech Univ Dept Mechatron Engn TR-34349 Istanbul Turkey Fdn Bruno Kessler Deep Visual Learning DVL Lab Trento Italy Ist Italiano Tecnol IIT Pattern Anal & Comp Vis PAVIS Visual Geometry & Modelling VGM Genoa Italy

Re-identifying objects in a rigid scene across varying viewpoints (object Re-ID) is a challenging task, in particular when there are similar, even identical objects coexist in the same environment. Discriminative features play no doubt an essential role in addressing this challenge, while for practical deployment, real-time performance is another desired attribute. We therefore propose a novel framework, named Fast re-OBJ, that is able to improve both Re-ID accuracy and processing speed via tight coupling between the instance segmentation module and embedding generation module. The rich object encoding in the instance segmentation backbone is directly shared to the embedding generation module for training a more discriminative representation via a triplet network. Moreover, we create datasets with the segmentation outputs using real-time object detectors to train and evaluate our object embedding module. With extensive experiments, we prove that our proposed Fast re-OBJ improves the object Re-ID accuracy by 5% and the speed is 5 x faster compared to the state-of-the-art methods. The dataset and code repository are publicly available at: https://***/bdsb53c4.

关键词： Object re-identification Embedding Triplet network Real-time Ranking

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FUSION AND ORTHOGONAL PROJECTION FOR IMPROVED FACE-VOICE ASSOCIATION 47

FUSION AND ORTHOGONAL PROJECTION FOR IMPROVED FACE-VOICE ASS...

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47th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

作者： Saeed, Muhammad Saad Khan, Muhammad Haris Nawaz, Shah Yousaf, Muhammad Haroon Del Bue, Alessio Univ Engn & Technol Taxila Swarm Robot Lab SRL NCRA Rawalpindi India Mohamed Bin Zayed Univ Artificial Intelligence Abu Dhabi U Arab Emirates Ist Italiano Tecnol IIT Pattern Anal & Comp Vis PAVIS Genoa Italy Ist Italiano Tecnol IIT Visual Geometry & Modelling VGM Genoa Italy Deutsch Elektronen Synchrotron DESY Hamburg Germany

ISBN: (纸本)9781665405409

We study the problem of learning association between face and voice. Prior works adopt pairwise or triplet loss formulations to learn an embedding space amenable for associated matching and verification tasks. Albeit showing some progress, such loss formulations are restrictive due to dependency on distance-dependent margin parameter, poor runtime training complexity, and reliance on carefully crafted negative mining procedures. In this work, we hypothesize that enriched feature representation coupled with an effective yet efficient supervision is necessary in realizing a discriminative joint embedding space for improved face-voice association. To this end, we propose a light-weight, plug-and-play mechanism that exploits the complementary cues in both modalities to form enriched fused embeddings and clusters them based on their identity labels via orthogonality constraints. We coin our proposed mechanism as fusion and orthogonal projection (FOP) and instantiate in a two-stream pipeline. The overall resulting framework is evaluated on a large-scale VoxCeleb dataset with a multitude of tasks, including cross-modal verification and matching. Our method performs favourably against the current state-of-the-art methods and our proposed supervision formulation is more effective and efficient than the ones employed by the contemporary methods.

关键词： Multimodal Face-voice association Cross-modal verification and matching

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Machine Learning for Cultural Heritage: A Survey

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PATTERN RECOGNITION LETTERS 2020年 133卷 102-108页

作者： Fiorucci, Marco Khoroshiltseva, Marina Pontil, Massimiliano Traviglia, Arianna Del Bue, Alessio James, Stuart Ist Italiano Tecnol IIT Ctr Cultural Heritage Technol CCHT Genoa Italy Ist Italiano Tecnol IIT Computat Stat & Machine Learning Genoa Italy Ist Italiano Tecnol IIT Visual Geometry & Modelling VGM Lab Genoa Italy

The application of Machine Learning (ML) to Cultural Heritage (CH) has evolved since basic statistical approaches such as Linear Regression to complex Deep Learning models. The question remains how much of this actively improves on the underlying algorithm versus using it within a 'black box' setting. We survey across ML and CH literature to identify the theoretical changes which contribute to the algorithm and in turn them suitable for CH applications. Alternatively, and most commonly, when there are no changes, we review the CH applications, features and pre/post-processing which make the algorithm suitable for its use. We analyse the dominant divides within ML, Supervised, Semi-supervised and Unsupervised, and reflect on a variety of algorithms that have been extensively used. From such an analysis, we give a critical look at the use of ML in CH and consider why CH has only limited adoption of ML. (C) 2020 The Authors. Published by Elsevier B.V.

关键词： Artificial Intelligence Machine Learning Cultural Heritage Digital Humanities

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