Correspondence-free online human motion retargeting

We present a novel data-driven framework for unsupervised human motion retargeting which animates a target body shape with a source motion. This allows to retarget motions between different characters by animating a target subject with a motion of a source subject. Our method is correspondence-free, i.e. neither spatial correspondences between the source and target shapes nor temporal correspondences between different frames of the source motion are required. Our proposed method directly animates a target shape with arbitrary sequences of humans in motion, possibly captured using 4D acquisition platforms or consumer devices. Our framework takes into account longterm temporal context of 1 second during retargeting while accounting for surface details. To achieve this, we take inspiration from two lines of existing work: skeletal motion retargeting, which leverages long-term temporal context at the cost of surface detail, and surface-based retargeting, which preserves surface details without considering longterm temporal context. We unify the advantages of these works by combining a learnt skinning field with a skeletal retargeting approach. During inference, our method runs online, i.e. the input can be processed in a serial way, and retargeting is performed in a single forward pass per frame. Experiments show that including long-term temporal context during training improves the method's accuracy both in terms of the retargeted skeletal motion and the detail preservation. Furthermore, our method generalizes well on unobserved motions and body shapes. We demonstrate that the proposed framework achieves state-of-the-art results on two test datasets

4DHumanOutfit: a multi-subject 4D dataset of human motion sequences in varying outfits exhibiting large displacements

This work presents 4DHumanOutfit, a new dataset of densely sampled spatio-temporal 4D human motion data of different actors, outfits and motions. The dataset is designed to contain different actors wearing different outfits while performing different motions in each outfit. In this way, the dataset can be seen as a cube of data containing 4D motion sequences along 3 axes with identity, outfit and motion. This rich dataset has numerous potential applications for the processing and creation of digital humans, e.g. augmented reality, avatar creation and virtual try on. 4DHumanOutfit is released for research purposes at https://kinovis.inria.fr/4dhumanoutfit/. In addition to image data and 4D reconstructions, the dataset includes reference solutions for each axis. We present independent baselines along each axis that demonstrate the value of these reference solutions for evaluation tasks

Fuzz-Web: A Methodology Based on Fuzzy Logic for Assessing Web Sites

Abstract: This paper presents a quality assessment methodology and model that measure the performance of dynamic websites. Called Fuzz-Web, a system that shows a comprehensive and natural manner of reasoning based on Multiple Criteria Decision Making process. We attempt so to use fuzzy logic as an intelligent technology, since the evaluation process is characterized by subjectivity and imprecision. Obviously, a phase of selecting appropriate evaluation criteria is necessary for the decision making process. Some tests realized on a set of Tunisian and foreign websites allow us to discuss the proposed reduced fuzzy method and then to validate the decision making result

Analyse d'un problème de tournée de véhicules avec gestion de stock dans un contexte de stock de consignation

International audienceRESUME : Le problème de tournées de véhicules avec gestion de stock (IRP) consiste à déterminer le circuit de distribution, d'un entrepôt central vers un ensemble de clients, qui optimise conjointement les coûts de transport et de stockage. Plusieurs travaux montrent l'intérêt de politiques comme le transbordement (transhipment) ou les tournées dynamiques sur les performances du système. Cependant, dans la pratique, ces politiques sont généralement critiquées car elles introduisent des contraintes additionnelles. Dans ce travail, nous étudions un problème IRP dans un contexte de stock de consignation. Nous montrons que le fonctionnement avec un stock de consignation justifie le recours à de telles politiques (transbordement, tournées dynamiques). Nous nous intéressons au cas de tournées statiques et nous montrons sur un exemple numérique que le transbordement permet de mieux optimiser ces tournées et d'améliorer ainsi les performances globales du système. MOTS-CLES : Tournée de véhicule avec gestion de stock, Stock de consignation, Transbordement

Analyse d'un problème de tournée de véhicules avec gestion de stock dans un contexte de stock de consignation

International audienceRESUME : Le problème de tournées de véhicules avec gestion de stock (IRP) consiste à déterminer le circuit de distribution, d'un entrepôt central vers un ensemble de clients, qui optimise conjointement les coûts de transport et de stockage. Plusieurs travaux montrent l'intérêt de politiques comme le transbordement (transhipment) ou les tournées dynamiques sur les performances du système. Cependant, dans la pratique, ces politiques sont généralement critiquées car elles introduisent des contraintes additionnelles. Dans ce travail, nous étudions un problème IRP dans un contexte de stock de consignation. Nous montrons que le fonctionnement avec un stock de consignation justifie le recours à de telles politiques (transbordement, tournées dynamiques). Nous nous intéressons au cas de tournées statiques et nous montrons sur un exemple numérique que le transbordement permet de mieux optimiser ces tournées et d'améliorer ainsi les performances globales du système. MOTS-CLES : Tournée de véhicule avec gestion de stock, Stock de consignation, Transbordement

Inventory routing problems in a context of vendor-managed inventory system with consignment stock and transshipment

International audienceThe inventory routing problem involves the integration and the coordination of two components of the logistics value chain: the inventory management and the vehicle routing decisions. In fact, the aim is to jointly decide on the distribution tour, from a distribution centre to a set of locations, and on the inventory policy for each location. Although many research investigations show great interest in policies such as transshipment or dynamic routings on the distribution system performances, these approaches are often criticised in practice as being too restrictive. In this article, we consider the inventory routing framework in a supplier integration context, i.e. a vendor-managed inventory with a consignment stock policy. Under such framework, we show that the transshipment brings more benefits than the classical context. In particular, we consider the case of static routings and we numerically show that transshipment permits to better optimise the distribution tours and to improve the global performance of the supply network

Impact of merging activities in a supply chain under the Guaranteed Service Model: Centralized and decentralized cases

International audienc

A hybrid approach combining cnns and variational modelling for blind image denoising

We consider the problem of image denoising with unknown noise distribution. We propose a hybrid approach where model-based space-variant total variation (TV) regularization is used for denoising with hyperparameters estimated locally using a Convolutional Neural Network (CNN) with a simple and light architecture. The special choice of the weighted TV prior allows for the use of a limited learning set, while the use of the proposed CNN approach allows for local parameter estimation independently of the type of noise in the data. The obtained results show that the proposed hybrid approach takes benefit from both the prior information encoded in the choice of the regularization model and the versatility of the CNN-based parameter estimation approach

Heuristic Algorithm for the Safety Stock Placement Problem

International audienc