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Author (down) Ignasi Rius; Dani Rowe; Jordi Gonzalez; Xavier Roca
Title 3D Action Modeling and Reconstruction for 2D Human Body Tracking Type Miscellaneous
Year 2005 Publication 3rd International Conference on Advances in Pattern Recognition (ICAPR’2005), Pattern Recognition and Image Analysis, LNCS 3687: 146–154, ISBN 978–3–540–28833–6 Abbreviated Journal
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Address Bath (United Kingdom)
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Notes ISE Approved no
Call Number ISE @ ise @ RRG2005c Serial 578
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Author (down) Hugo Prol; Vincent Dumoulin; Luis Herranz
Title Cross-Modulation Networks for Few-Shot Learning Type Miscellaneous
Year 2018 Publication Arxiv Abbreviated Journal
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Abstract A family of recent successful approaches to few-shot learning relies on learning an embedding space in which predictions are made by computing similarities between examples. This corresponds to combining information between support and query examples at a very late stage of the prediction pipeline. Inspired by this observation, we hypothesize that there may be benefits to combining the information at various levels of abstraction along the pipeline. We present an architecture called Cross-Modulation Networks which allows support and query examples to interact throughout the feature extraction process via a feature-wise modulation mechanism. We adapt the Matching Networks architecture to take advantage of these interactions and show encouraging initial results on miniImageNet in the 5-way, 1-shot setting, where we close the gap with state-of-the-art.
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Notes LAMP; 600.120 Approved no
Call Number Admin @ si @ PDH2018 Serial 3248
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Author (down) Hugo Jair Escalante; Heysem Kaya; Albert Ali Salah; Sergio Escalera; Yagmur Gucluturk; Umut Guclu; Xavier Baro; Isabelle Guyon; Julio C. S. Jacques Junior; Meysam Madadi; Stephane Ayache; Evelyne Viegas; Furkan Gurpinar; Achmadnoer Sukma Wicaksana; Cynthia C. S. Liem; Marcel A. J. van Gerven; Rob van Lier
Title Explaining First Impressions: Modeling, Recognizing, and Explaining Apparent Personality from Videos Type Miscellaneous
Year 2018 Publication Arxiv Abbreviated Journal
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Abstract Explainability and interpretability are two critical aspects of decision support systems. Within computer vision, they are critical in certain tasks related to human behavior analysis such as in health care applications. Despite their importance, it is only recently that researchers are starting to explore these aspects. This paper provides an introduction to explainability and interpretability in the context of computer vision with an emphasis on looking at people tasks. Specifically, we review and study those mechanisms in the context of first impressions analysis. To the best of our knowledge, this is the first effort in this direction. Additionally, we describe a challenge we organized on explainability in first impressions analysis from video. We analyze in detail the newly introduced data set, the evaluation protocol, and summarize the results of the challenge. Finally, derived from our study, we outline research opportunities that we foresee will be decisive in the near future for the development of the explainable computer vision field.
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Notes HUPBA Approved no
Call Number Admin @ si @ JKS2018 Serial 3095
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Author (down) Hao Wu; Alejandro Ariza-Casabona; Bartłomiej Twardowski; Tri Kurniawan Wijaya
Title MM-GEF: Multi-modal representation meet collaborative filtering Type Miscellaneous
Year 2023 Publication ARXIV Abbreviated Journal
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Abstract In modern e-commerce, item content features in various modalities offer accurate yet comprehensive information to recommender systems. The majority of previous work either focuses on learning effective item representation during modelling user-item interactions, or exploring item-item relationships by analysing multi-modal features. Those methods, however, fail to incorporate the collaborative item-user-item relationships into the multi-modal feature-based item structure. In this work, we propose a graph-based item structure enhancement method MM-GEF: Multi-Modal recommendation with Graph Early-Fusion, which effectively combines the latent item structure underlying multi-modal contents with the collaborative signals. Instead of processing the content feature in different modalities separately, we show that the early-fusion of multi-modal features provides significant improvement. MM-GEF learns refined item representations by injecting structural information obtained from both multi-modal and collaborative signals. Through extensive experiments on four publicly available datasets, we demonstrate systematical improvements of our method over state-of-the-art multi-modal recommendation methods.
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Notes LAMP Approved no
Call Number Admin @ si @ WAT2023 Serial 3988
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Author (down) Hannes Mueller; Andre Groger; Jonathan Hersh; Andrea Matranga; Joan Serrat
Title Monitoring War Destruction from Space: A Machine Learning Approach Type Miscellaneous
Year 2020 Publication Arxiv Abbreviated Journal
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Abstract Existing data on building destruction in conflict zones rely on eyewitness reports or manual detection, which makes it generally scarce, incomplete and potentially biased. This lack of reliable data imposes severe limitations for media reporting, humanitarian relief efforts, human rights monitoring, reconstruction initiatives, and academic studies of violent conflict. This article introduces an automated method of measuring destruction in high-resolution satellite images using deep learning techniques combined with data augmentation to expand training samples. We apply this method to the Syrian civil war and reconstruct the evolution of damage in major cities across the country. The approach allows generating destruction data with unprecedented scope, resolution, and frequency – only limited by the available satellite imagery – which can alleviate data limitations decisively.
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Notes ADAS; 600.118 Approved no
Call Number Admin @ si @ MGH2020 Serial 3489
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Author (down) Guillem Cucurull; Pau Rodriguez; Vacit Oguz Yazici; Josep M. Gonfaus; Xavier Roca; Jordi Gonzalez
Title Deep Inference of Personality Traits by Integrating Image and Word Use in Social Networks Type Miscellaneous
Year 2018 Publication Arxiv Abbreviated Journal
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Abstract arXiv:1802.06757
Social media, as a major platform for communication and information exchange, is a rich repository of the opinions and sentiments of 2.3 billion users about a vast spectrum of topics. To sense the whys of certain social user’s demands and cultural-driven interests, however, the knowledge embedded in the 1.8 billion pictures which are uploaded daily in public profiles has just started to be exploited since this process has been typically been text-based. Following this trend on visual-based social analysis, we present a novel methodology based on Deep Learning to build a combined image-and-text based personality trait model, trained with images posted together with words found highly correlated to specific personality traits. So the key contribution here is to explore whether OCEAN personality trait modeling can be addressed based on images, here called MindPics, appearing with certain tags with psychological insights. We found that there is a correlation between those posted images and their accompanying texts, which can be successfully modeled using deep neural networks for personality estimation. The experimental results are consistent with previous cyber-psychology results based on texts or images.
In addition, classification results on some traits show that some patterns emerge in the set of images corresponding to a specific text, in essence to those representing an abstract concept. These results open new avenues of research for further refining the proposed personality model under the supervision of psychology experts.
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Notes ISE; 600.098; 600.119 Approved no
Call Number Admin @ si @ CRY2018 Serial 3550
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Author (down) German Barquero; Sergio Escalera; Cristina Palmero
Title Seamless Human Motion Composition with Blended Positional Encodings Type Miscellaneous
Year 2024 Publication Arxiv Abbreviated Journal
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Abstract Conditional human motion generation is an important topic with many applications in virtual reality, gaming, and robotics. While prior works have focused on generating motion guided by text, music, or scenes, these typically result in isolated motions confined to short durations. Instead, we address the generation of long, continuous sequences guided by a series of varying textual descriptions. In this context, we introduce FlowMDM, the first diffusion-based model that generates seamless Human Motion Compositions (HMC) without any postprocessing or redundant denoising steps. For this, we introduce the Blended Positional Encodings, a technique that leverages both absolute and relative positional encodings in the denoising chain. More specifically, global motion coherence is recovered at the absolute stage, whereas smooth and realistic transitions are built at the relative stage. As a result, we achieve state-of-the-art results in terms of accuracy, realism, and smoothness on the Babel and HumanML3D datasets. FlowMDM excels when trained with only a single description per motion sequence thanks to its Pose-Centric Cross-ATtention, which makes it robust against varying text descriptions at inference time. Finally, to address the limitations of existing HMC metrics, we propose two new metrics: the Peak Jerk and the Area Under the Jerk, to detect abrupt transitions.
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Notes HUPBA Approved no
Call Number Admin @ si @ BEP2024 Serial 4022
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Author (down) George A. Triantafyllid; Nikolaos Thomos; Cristina Cañero; P. Vieyres; Michael G. Strintzis
Title A User Interface for Mobile Robotized Tele-Echography Type Miscellaneous
Year 2005 Publication 3rd International Conference on Imaging Technologies in Biomedical Sciences (ITBS 2005) Abbreviated Journal
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Address Milos Island (Greece)
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Notes Approved no
Call Number Admin @ si @ TTC2005 Serial 587
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Author (down) Georg Langs; Petia Radeva; David Rotger; Francesc Carreras
Title Building and Registering Parameterized 3D Models of Vessel Trees for Visualization during Intervention Type Miscellaneous
Year 2004 Publication 17th International Conference on Pattern Recognition, ICPR’04 Abbreviated Journal
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Address Cambridge, United Kingdom
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Notes MILAB Approved no
Call Number BCNPCL @ bcnpcl @ LRR2004b Serial 463
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Author (down) Georg Langs; Petia Radeva; David Rotger; Francesc Carreras
Title Explorative Building of 3D Vessel Tree Models Type Miscellaneous
Year 2004 Publication “Digital Imaging in Media and Education”, 28th annual workshop of the Austrian Association for Pattern Recognition (OAGM/AAPR) Abbreviated Journal
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Address Hagenberg (Austria)
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Notes MILAB Approved no
Call Number BCNPCL @ bcnpcl @ LRR2004a Serial 467
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Author (down) Gemma Sanchez; Josep Llados; K. Tombre
Title An Algorithm to Recognize Graphical Textured Symbols using String Representations. Type Miscellaneous
Year 2001 Publication Proceedings of the IX Spanish Symposium on Pattern Recognition and Image Analysis, :203–208. Abbreviated Journal
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Notes DAG Approved no
Call Number DAG @ dag @ SLT2001a Serial 163
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Author (down) Gemma Sanchez; Josep Llados; K. Tombre
Title An Error-Correction Graph Grammar to Recognize Textured Symbols. Type Miscellaneous
Year 2001 Publication Fourth IAPR International Workshop on Graphics Recognition, GREC 2001, 135–146. Abbreviated Journal
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Address Canada
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Notes DAG Approved no
Call Number DAG @ dag @ SLT2001b Serial 164
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Author (down) Gemma Sanchez; Josep Llados
Title A Graph Grammar to Recognize Textured Symbols. Type Miscellaneous
Year 2001 Publication Sixth International Conference on Document Analysis and Recognition, ICDAR 2001, 465–469. Abbreviated Journal
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Address USA
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Notes DAG Approved no
Call Number DAG @ dag @ SLl2001 Serial 162
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Author (down) Gemma Sanchez; Josep Llados
Title Syntactic models to represent perceptually regular repetitive patterns in graphic documents Type Miscellaneous
Year 2003 Publication Proceedings of Fifth IAPR International Workshop on Graphics Recognition, 194–201 Abbreviated Journal
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Address Barcelona
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Notes DAG Approved no
Call Number DAG @ dag @ SaL2003 Serial 417
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Author (down) Gemma Sanchez; Josep Llados
Title Syntactic models to represent perceptually regular repetitive patterns in graphic documents Type Miscellaneous
Year 2004 Publication Graphics Recognition: Recent Advances and Perspectives, Lecture Notes in Computer Science, J. Llados, Y.B. Kwon (Eds.), 3088:162–171 Abbreviated Journal
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Address Springer-Verlag
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Notes DAG Approved no
Call Number DAG @ dag @ SaL2004 Serial 462
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