Browsing by Author "Loscos, Celine"

Now showing 1 - 7 of 7
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    3D Human Shape and Pose from a Single Depth Image with Deep Dense Correspondence Enabled Model Fitting
    (The Eurographics Association, 2022) Wang, Xiaofang; Boukhayma, Adnane; Prévost, Stéphanie; Desjardin, Eric; Loscos, Celine; Multon, Franck; Sauvage, Basile; Hasic-Telalovic, Jasminka
    We propose a two-stage hybrid method, with no initialization, for 3D human shape and pose estimation from a single depth image, combining the benefits of deep learning and optimization. First, a convolutional neural network predicts pixel-wise dense semantic correspondences to a template geometry, in the form of body part segmentation labels and normalized canonical geometry vertex coordinates. Using these two outputs, pixel-to-vertex correspondences are computed in a six-dimensional embedding of the template geometry through nearest neighbor. Second, a parametric shape model (SMPL) is fitted to the depth data by minimizing vertex distances to the input. Extensive evaluation on both real and synthetic human shape in motion datasets shows that our method yields quantitatively and qualitatively satisfactory results and state-of-the-art reconstruction errors.
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    Consistent Multi- and Single-View HDR-Image Reconstruction from Single Exposures
    (The Eurographics Association, 2022) Mohan, Aditya; Zhang, Jing; Cozot, Rémi; Loscos, Celine; Sauvage, Basile; Hasic-Telalovic, Jasminka
    We propose a CNN-based approach for reconstructing HDR images from just a single exposure. It predicts the saturated areas of LDR images and then blends the linearized input with the predicted outputs. Two loss functions are used: the Mean Absolute Error and the Multi-Scale Structural Similarity Index. The choice of these loss functions allows us to outperform previous algorithms in the reconstructed dynamic range. Once the network trained, we input multi-view images to it to output multi-view coherent images.
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    Consistent Multi- and Single-View HDR-Image Reconstruction from Single Exposures
    (The Eurographics Association, 2022) Mohan, Aditya; Zhang, Jing; Cozot, Remi; Loscos, Celine; Ronfard, Rémi; Wu, Hui-Yin
    Recently, there have been attempts to obtain high-dynamic range (HDR) images from single exposures and efforts to reconstruct multi-view HDR images using multiple input exposures. However, there have not been any attempts to reconstruct multi-view HDR images from multi-view Single Exposures to the best of our knowledge. We present a two-step methodology to obtain color consistent multi-view HDR reconstructions from single-exposure multi-view low-dynamic-range (LDR) Images. We define a new combination of the Mean Absolute Error and Multi-Scale Structural Similarity Index loss functions to train a network to reconstruct an HDR image from an LDR one. Once trained we use this network to multi-view input. When tested on single images, the outputs achieve competitive results with the state-of-the-art. Quantitative and qualitative metrics applied to our results and to the state-of-the-art show that our HDR expansion is better than others while maintaining similar qualitative reconstruction results. We also demonstrate that applying this network on multi-view images ensures coherence throughout the generated grid of HDR images.
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    Fast and Fine Disparity Reconstruction for Wide-baseline Camera Arrays with Deep Neural Networks
    (The Eurographics Association, 2022) Barrios, Théo; Gerhards, Julien; Prévost, Stéphanie; Loscos, Celine; Sauvage, Basile; Hasic-Telalovic, Jasminka
    Recently, disparity-based 3D reconstruction for stereo camera pairs and light field cameras have been greatly improved with the uprising of deep learning-based methods. However, only few of these approaches address wide-baseline camera arrays which require specific solutions. In this paper, we introduce a deep-learning based pipeline for multi-view disparity inference from images of a wide-baseline camera array. The network builds a low-resolution disparity map and retains the original resolution with an additional up scaling step. Our solution successfully answers to wide-baseline array configurations and infers disparity for full HD images at interactive times, while reducing quantification error compared to the state of the art.
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    From Capture to Immersive Viewing of 3D HDR Point Clouds
    (The Eurographics Association, 2022) Loscos, Celine; Souchet, Philippe; Barrios, Théo; Valenzise, Giuseppe; Cozot, Rémi; Hahmann, Stefanie; Patow, Gustavo A.
    The collaborators of the ReVeRY project address the design of a specific grid of cameras, a cost-efficient system that acquires at once several viewpoints, possibly under several exposures and the converting of multiview, multiexposed, video stream into a high quality 3D HDR point cloud. In the last two decades, industries and researchers proposed significant advances in media content acquisition systems in three main directions: increase of resolution and image quality with the new ultra-high-definition (UHD) standard; stereo capture for 3D content; and high-dynamic range (HDR) imaging. Compression, representation, and interoperability of these new media are active research fields in order to reduce data size and be perceptually accurate. The originality of the project is to address both HDR and depth through the entire pipeline. Creativity is enhanced by several tools, which answer challenges at the different stages of the pipeline: camera setup, data processing, capture visualisation, virtual camera controller, compression, perceptually guided immersive visualisation. It is the experience acquired by the researchers of the project that is exposed in this tutorial.
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    Introduction to Computer Graphics: A Visual Interactive Approach
    (The Eurographics Association, 2022) Loscos, Celine; Bourdin, Jean-Jacques; Paquette, Eric
    Computer graphics is a difficult topic, requiring associating mathematics and programming skills. When initially taught at undergraduate levels, there are several factors which discourage students. First, programming a first computer graphics program requires a substantial initial framework which can be intimidating for many of them. Second, understanding and applying mathematical concepts is very often overwhelming. To counter this intimidating feeling, a new teaching approach was proposed in 2018 to 3rd year undergraduate computer science students. The course was split into two parts, theory and practice. The theoretical concepts were seen in class, with course handouts and table exercises resembling closely to traditional computer graphics learning. The originality of the course comes from a new way of practicing 3D programming. Practical labs were built upon the Unity game engine programming platform, adapted to match the theoretical concepts seen in classroom. Conclusions are drawn over 4 years of teaching this course. When taught using an accompanying easy-to-access graphics programming platform, computer graphics becomes a more attractive course for students with lower mathematics and programming skills. It is also very satisfactory for skillful students as it enables them to grab and master concepts quickly to reach interesting final lab achievements.
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    Safeguarding our Dance Cultural Heritage
    (The Eurographics Association, 2022) Aristidou, Andreas; Chalmers, Alan; Chrysanthou, Yiorgos; Loscos, Celine; Multon, Franck; Parkins, J. E.; Sarupuri, Bhuvan; Stavrakis, Efstathios; Hahmann, Stefanie; Patow, Gustavo A.
    Folk dancing is a key aspect of intangible cultural heritage that often reflects the socio-cultural and political influences prevailing in different periods and nations; each dance produces a meaning, a story with the help of music, costumes and dance moves. It has been transmitted from generation to generation, and to different countries, mainly due to movements of people carrying and disseminating their civilization. However, folk dancing, amongst other intangible heritage, is at high risk of disappearing due to wars, the moving of populations, economic crises, modernization, but most importantly, because these fragile creations have been modified over time through the process of collective recreation, and/or changes in the way of life. In this tutorial, we show how the European Project, SCHEDAR, exploited emerging technologies to digitize, analyze, and holistically document our intangible heritage creations, that is a critical necessity for the preservation and the continuity of our identity as Europeans.