Diane Larlus
Computer Vision & Machine Learning Research Scientist
Publications
  • ARTEMIS: Attention-based Retrieval with Text-Explicit Matching and Implicit Similarity. Ginger Delmas, Rafael Sampaio de Rezende, Gabriela Csurka, Diane Larlus. ICLR 2022
  • Learning Super-Features for Image Retrieval. Philippe Weinzaepfel, Thomas Lucas, Diane Larlus, Yannis Kalantidis. ICLR 2022
  • NeuralDiff: Segmenting 3D objects that move in egocentric videos. Vadim Tschernezki, Diane Larlus, Andrea Vedaldi. 3DV 2021
  • Probabilistic Embeddings for Cross-Modal Retrieval. Sanghyuk Chun, Seong Joon Oh, Rafael Sampaio de Rezende, Yannis Kalantidis, Diane Larlus. CVPR 2021 [paper, code]
  • Unsupervised Meta-Domain Adaptation for Fashion Retrieval. Vivek Sharma, Naila Murray, Diane Larlus, Saquib Sarfraz, Rainer Stiefelhagen, Gabriela Csurka. WACV 2021
  • StacMR: Scene-Text Aware Cross-Modal Retrieval. Andres Mafla, Rafael Sampaio de Rezende, Lluis Gomez, Diane Larlus, Dimosthenis Karatzas. WACV 2021
  • Hard negative mixing for contrastive learning. Yannis Kalantidis, Mert Bülent Sariyildiz, Noé Pion, Philippe Weinzaepfel, Diane Larlus. NeurIPS 2020
  • Learning Visual Representations with Caption Annotations. Mert Bülent Sariyildiz, Julien Perez, Diane Larlus. ECCV 2020
  • Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings. Michael Wray, Diane Larlus, Gabriela Csurka, Dima Damen. ICCV 2019
  • Capturing the geometry of object categories from video supervision. David Novotny, Diane Larlus, Andrea Vedaldi. PAMI 2018
  • Semi-convolutional Operators for Instance Segmentation. David Novotny, Samuel Albanie, Diane Larlus, Andrea Vedaldi. ECCV 2018
  • Self-supervised learning of geometrically stable features through probabilistic introspection. David Novotny, Samuel Albanie, Diane Larlus, Andrea Vedaldi. CVPR 2018
  • Learning 3D Object Categories by Looking Around Them. David Novotny, Diane Larlus, Andrea Vedaldi. ICCV 2017 [Video,arXiv]
  • End-to-end learning of deep visual representations for image retrieval. Albert Gordo, Jon Almaz’an, Jérôme Revaud, Diane Larlus. IJCV 2017
  • Beyond instance-level image retrieval: Leveraging captions to learn a global visual representation for semantic retrieval. Albert Gordo, Diane Larlus. CVPR 2017
  • AnchorNet: A Weakly Supervised Network to Learn Geometry-sensitive Features For Semantic Matching. David Novotny, Diane Larlus, Andrea Vedaldi. CVPR 2017
  • Generalizing Semantic Part Detectors Across Domains. David Novotny, Diane Larlus, Andrea Vedaldi. Domain Adaptation in Computer Vision Applications, Book Chapter (259-278) 2017
  • Deep image retrieval: Learning global representations for image search. Albert Gordo, Jon Almazán, Jérôme Revaud, Diane Larlus. ECCV 2016
  • Learning the structure of objects from web supervision. David Novotny, Diane Larlus, Andrea Vedaldi. ECCV Workshop 2016
  • I Have Seen Enough: Transferring Parts Across Categories. David Novotny, Diane Larlus, Andrea Vedaldi. BMVC 2016
  • Data-driven Detection of Prominent Objects. Jose Rodriguez-Serrano, Diane Larlus, Zhenwen Dai. TPAMI 2015
  • Fisher vectors meet neural networks: A hybrid classification architecture. Florent Perronnin, Diane Larlus. CVPR 2015
  • Predicting an Object Location Using a Global Image Representation. Jose Rodriguez Serrano, Diane Larlus. ICCV 2013
  • What is a good evaluation measure for semantic segmentation? Gabriela Csurka, Diane Larlus, Florent Perronnin. BMVC 2013
  • On the use of regions for semantic image segmentation. Rui Hu, Diane Larlus, Gabriela Csurka. ICVGIP 2012
  • Semantic image segmentation using visible and near-infrared channels? Neda Salamati, Diane Larlus, Gabriela Csurka, Sabine Süsstrunk. ECCV Workshop 2012.
  • Color naming. WR Benavente, M Vanrell, C Schmid, R Baldrich, J Verbeek, D Larlus. Color in Computer Vision: Fundamentals and Applications, Book Chapter (287-317) 2012
  • Évaluation automatique de la qualité esthétique des photographies à l’aide de descripteurs d’images génériques. L Marchesotti, F Perronnin, D Larlus, G Csurka, L Michallon. RFIA 2012
  • Assessing the aesthetic quality of photographs using generic image descriptors. L Marchesotti, F Perronnin, D Larlus, G Csurka. ICCV 2011
  • Weakly supervised recognition of daily life activities with wearable sensors. M Stikic, D Larlus, S Ebert, B Schiele. TPAMI 2011.
  • Combining Visible and Near-Infrared Cues for Image Categorisation. N Salamati, D Larlus, G Csurka. BMVC 2011
  • Manifold based local classifiers: Linear and nonlinear approaches. H Cevikalp, D Larlus, M Neamtu, B Triggs, F Jurie. Journal of Signal Processing Systems 2010
  • Extracting structures in image collections for object recognition. S Ebert, D Larlus, B Schiele. ECCV 2010
  • Category level object segmentation by combining bag-of-words models with dirichlet processes and random fields. D Larlus, J Verbeek, F Jurie. IJCV 2010
  • D’une collection d’images a sa structure semantique, vers un processus automatique. D Larlus, S Ebert, B Schiele. RFIA 2010
  • Standing on the Shoulders of Other Researchers A Position Statement. U Blanke, D Larlus, K Van Laerhoven, B Schiele. Pervasive Workshop 2010
  • Multi-graph based semi-supervised learning for activity recognition. M Stikic, D Larlus, B Schiele. WACV 2009 (Best paper award)
  • Learning color names for real-world applications. J Van De Weijer, C Schmid, J Verbeek, D Larlus. TIP 2009
  • Latent mixture vocabularies for object categorization and segmentation. D Larlus, F Jurie. Image and Vision Computing 2009
  • Treasure hunting for humanoids robot. O Stasse, T Foissotte, D Larlus, A Kheddar, K Yokoi. Humanoids 2008
  • Création et utilisation de vocabulaires visuels pour la catégorisation d’images et la segmentation de classes d’objets. D Larlus. PhD Thesis 2008
  • Combining appearance models and markov random fields for category level object segmentation. D Larlus, F Jurie. CVPR 2008
  • Segmentation de catégories d’objets par combinaison d’un modèle d’apparence et d’un champs de Markov. D Larlus, E Nowak, F Jurie. RFIA 2008
  • Towards autonomous object reconstruction for visual search by the humanoid robot hrp-2. O Stasse, D Larlus, B Lagarde, A Escande, F Saidi, A Kheddar, K Yokoi. Humanoids 2007
  • A supervised clustering algorithm for the initialization of rbf neural network classifiers. H Cevikalp, D Larlus, F Jurie. SPCA 2007
  • Category level object segmentation-learning to segment objects with latent aspect models. D Larlus, F Jurie. VISAPP 2007
  • Local subspace Classifiers: Linear and Non Linear Approaches. H Cevikalp, D Larlus, M Douze, J Jurie. Workshop on Machine Learning for Signal Processing 2007
  • Latent mixture vocabularies for object categorization. D Larlus, F Jurie. BMVC 2006
  • Learning saliency maps for object categorization. F Moosmann, D Larlus, F Jurie. ECCV Workshop 2006
  • Création de vocabulaires visuels efficaces pour la catégorisation d’images. D Larlus, G Dorkó, F Jurie. RFIA 2006

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