Number of documents

34

David Picard


MIDI   

Journal articles6 documents

  • Jerome Fellus, David Picard, Philippe-Henri Gosselin. Asynchronous gossip principal components analysis. Neurocomputing, Elsevier, 2015, pp.0. ⟨10.1016/j.neucom.2014.11.076⟩. ⟨hal-01148639⟩
  • Olivier Kihl, David Picard, Philippe-Henri Gosselin. A Unified framework for local visual descriptors evaluation. Pattern Recognition, Elsevier, 2015, 48, pp.1170-1180. ⟨10.1016/j.patcog.2014.11.013⟩. ⟨hal-01089310⟩
  • Olivier Kihl, David Picard, Philippe-Henri Gosselin. Local polynomial space–time descriptors for action classification. Machine Vision and Applications, Springer Verlag, 2014, pp.1-11. ⟨10.1007/s00138-014-0652-z⟩. ⟨hal-01097536⟩
  • David Picard, Nicolas Thome, Matthieu Cord. JKernelMachines: A Simple Framework for Kernel Machines. Journal of Machine Learning Research, Microtome Publishing, 2013, 14, pp.1417-1421. ⟨hal-00832030⟩
  • Romain Negrel, David Picard, Philippe-Henri Gosselin. Web scale image retrieval using compact tensor aggregation of visual descriptors. IEEE MultiMedia, Institute of Electrical and Electronics Engineers, 2013, 20 (3), pp.24-33. ⟨hal-00832760⟩
  • David Picard, Philippe-Henri Gosselin. Efficient image signatures and similarities using tensor products of local descriptors. Computer Vision and Image Understanding, Elsevier, 2013, 117 (6), pp.680-687. ⟨10.1016/j.cviu.2013.02.004⟩. ⟨hal-00799074⟩

Conference papers27 documents

  • Marie-Morgane Paumard, David Picard, Hedi Tabia. Jigsaw Puzzle Solving Using Local Feature Co-occurrences In Deep Neural Networks. International Conference on Image Processing, Oct 2018, Athens, Greece. ⟨hal-01820489v2⟩
  • Diogo Luvizon, David Picard, Hedi Tabia. 2D/3D Pose Estimation and Action Recognition using Multitask Deep Learning. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Jun 2018, Salt Lake City, United States. ⟨hal-01815703⟩
  • Pierre Jacob, David Picard, Aymeric Histace, Edouard Klein. Leveraging Implicit Spatial Information In Global Features For Image Retrieval . IEEE International Conference in Image Processing, Oct 2018, Athens, Greece. ⟨hal-01816918⟩
  • Diogo Luvizon, Hedi Tabia, David Picard. Multimodal Deep Neural Networks for Pose Estimation and Action Recognition. Congrès Reconnaissance des Formes, Image, Apprentissage et Perception (RFIAP 2018), Jun 2018, Marne-la-Vallée, France. ⟨hal-01815707⟩
  • Jerome Fellus, David Picard, Philippe-Henri Gosselin. Asynchronous decentralized convex optimization through short-term gradient averaging. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Apr 2015, Bruges, Belgium. ⟨hal-01148648⟩
  • Nicolas Cazin, Aymeric Histace, David Picard, Benoît Gaudou. On The Joint Modeling of The Behavior of Social Insects and Their Interaction With Environment by Taking Into Account Physical Phenomena Like Anisotropic Diffusion. International Conference on Practical Applications of Agents and Multi-Agent Systems, Jun 2015, Salamanque, Spain. pp.151-164. ⟨hal-01127710⟩
  • Hedi Tabia, Hamid Laga, David Picard, Philippe-Henri Gosselin. Covariance Descriptors for 3D Shape Matching and Retrieval. IEEE Conference on Computer Vsion and Pattern Recognition, Jun 2014, Columbus, Ohio, United States. 8 p. ⟨hal-01022970⟩
  • Romain Negrel, David Picard, Philippe-Henri Gosselin. Evaluation of Second-order Visual Features for Land-Use Classification. 12th International Workshop on Content-Based Multimedia Indexing, Jun 2014, France. 5 p. ⟨hal-01022971⟩
  • Romain Negrel, David Picard, Philippe-Henri Gosselin. Efficient Dimension Reduction Of Global Signature With Sparse Projectors For Image Near Duplicate Retrieval. IAPR International Conference on Pattern Recognition, Aug 2014, Stockholm, Sweden. 6 p. ⟨hal-01064050⟩
  • Romain Negrel, David Picard, Philippe-Henri Gosselin. DIMENSIONALITY REDUCTION OF VISUAL FEATURES USING SPARSE PROJECTORS FOR CONTENT-BASED IMAGE RETRIEVAL. IEEE International Conference on Image Processing, Oct 2014, Paris, France. pp.2192-2196. ⟨hal-01081770⟩
  • Jérôme Fellus, David Picard, Philippe-Henri Gosselin. Dimensionality reduction in decentralized networks by Gossip aggregation of principal components analyzers. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Apr 2014, Bruges, Belgium. pp.171-176. ⟨hal-00985721⟩
  • David Picard, Ngoc-Son Vu, Inbar Fijalkow. PHOTOGRAPHIC PAPER TEXTURE CLASSIFICATION USING MODEL DEVIATION OF LOCAL VISUAL DESCRIPTORS. IEEE Int. Conf. on Image Processing, Oct 2014, Paris, France, France. 5 p. ⟨hal-01063123⟩
  • Philippe-Henri Gosselin, David Picard. Machine Learning and Content-Based Multimedia Retrieval. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Apr 2013, Bruges, Belgium. pp.251-260. ⟨hal-00864824⟩
  • Olivier Kihl, David Picard, Philippe-Henri Gosselin. A Unified Formalism for Video Descriptors. IEEE Int. Conf. on Image Processing ICIP2013, Sep 2013, Melbourne, Australia. pp.2416-2419. ⟨hal-00832190v2⟩
  • Mehdi Badr, Dan Vodislav, David Picard, Shaoyi Yin, Philippe-Henri Gosselin. Multi-criteria Search Algorithm: An Efficient Approximate K-NN Algorithm for Image Retrieval. IEEE Int. Conf. on Image Processing ICIP2013, Sep 2013, Melbourne, Australia. pp.2901-2905, ⟨10.1109/ICIP.2013.6738597⟩. ⟨hal-00832196v2⟩
  • Hedi Tabia, David Picard, Hamid Laga, Philippe-Henri Gosselin. Fast Approximation of Distance Between Elastic Curves using Kernels. British Machine Vision Conference, Sep 2013, United Kingdom. pp.11. ⟨hal-00861369⟩
  • Jérôme Fellus, David Picard, Philippe-Henri Gosselin. Calcul décentralisé de dictionnaires visuels pour l'indexation multimédia dans les bases de données réparties sur les réseaux. ORASIS : Orasis, Congrès des jeunes chercheurs en vision par ordinateur, Jun 2013, Cluny, France. ⟨hal-00807486⟩
  • Hedi Tabia, David Picard, Hamid Laga, Philippe-Henri Gosselin. 3D Shape Similarity Using Vectors of Locally Aggregated Tensors. IEEE International Conference on Image Processing, Sep 2013, Melbourne, Australia. pp.2694-2698. ⟨hal-00832182⟩
  • David Picard, Aymeric Histace, Marie-Charlotte Desseroit. Joint MAS-PDE Modeling of Forest Pest Insect Dynamics: Analysis of the Bark Beetle's Behavior. VISIGRAPP (Workshop GEODIFF), Feb 2013, Barcelone, Spain. pp.29-38. ⟨hal-00784160⟩
  • Jérôme Fellus, David Picard, Philippe-Henri Gosselin. Decentralized K-means using randomized Gossip protocols for clustering large datasets. International Workshop on Knowledge Discovery Using Cloud and Distributed Computing Platforms, Dec 2013, Dallas, Texas, United States. pp.8. ⟨hal-00915822⟩
  • Olivier Kihl, David Picard, Philippe-Henri Gosselin. Local polynomial space-time descriptors for actions classification. International Conference on Machine Vision Applications, May 2013, Kyoto, Japan. ⟨hal-00807493⟩
  • Hedi Tabia, David Picard, Hamid Laga, Philippe-Henri Gosselin. Compact Vectors of Locally Aggregated Tensors for 3D shape retrieval. Eurographics Workshop on 3D Object Retrieval, May 2013, Girona, Spain. ⟨hal-00807501⟩
  • Romain Negrel, David Picard, Philippe-Henri Gosselin. Compact Tensor Based Image Representation for Similarity Search. IEEE International Conference on Image Processing, Sep 2012, Orlando, United States. ⟨hal-00753157⟩
  • Romain Negrel, David Picard, Philippe-Henri Gosselin. Using Spatial Pyramids with Compacted VLAT for Image Categorization. International Conference on Pattern Recognition, Nov 2012, Tsukuba, Japan. ⟨hal-00753158⟩
  • David Picard, Nicolas Thome, Matthieu Cord, Alain Rakotomamonjy. Learning geometric combinations of Gaussian kernels with alternating Quasi-Newton algorithm. 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Apr 2012, Bruges, Belgium. pp.79-84. ⟨hal-00705374⟩
  • Corina Iovan, David Picard, Nicolas Thome, Matthieu Cord. Classification of Urban Scenes from Geo-referenced Images in Urban Street-View Context. Machine Learning and Applications (ICMLA), 2012 11th International Conference on, Dec 2012, Boca Raton, Florida, United States. pp.339--344. ⟨hal-00794980⟩
  • David Picard, Philippe-Henri Gosselin. Improving Image Similarity With Vectors of Locally Aggregated Tensors. 2011 IEEE International Conference on Image Processing (IEEE ICIP2011), Sep 2011, Brussels, Belgium. pp.669 - 672, ⟨10.1109/ICIP.2011.6116641⟩. ⟨hal-00591993⟩

Theses1 document

  • David Picard. Recherche d'images sur un réseau à l'aide d'un système multi-agents. Traitement du signal et de l'image [eess.SP]. Université de Cergy-Pontoise, 2008. Français. ⟨tel-01089722⟩