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Bibliography

Publications of the year

Doctoral Dissertations and Habilitation Theses

Articles in International Peer-Reviewed Journals

  • 2L. Amsaleg, M. E. Houle, E. Schubert.

    Introduction to Special Issue of the 9th International Conference on Similarity Search and Applications (SISAP 2016), in: Information Systems, February 2019, vol. 80, 107 p. [ DOI : 10.1016/j.is.2018.11.006 ]

    https://hal.inria.fr/hal-02106914
  • 3M. Cui, L. Li, M. Shi.

    A Selective Biogeography-Based Optimizer Considering Resource Allocation for Large-Scale Global Optimization, in: Computational Intelligence and Neuroscience, July 2019, pp. 1-18. [ DOI : 10.1155/2019/1240162 ]

    https://hal.inria.fr/hal-02383076
  • 4C. Dalloux, N. Grabar, V. Claveau.

    Detecting negation: machine learning and a corpus for French, in: Revue des Sciences et Technologies de l'Information - Série TSI : Technique et Science Informatiques, December 2019, pp. 1-21.

    https://hal.archives-ouvertes.fr/hal-02402913
  • 5S. Li, X. Song, H. Lu, L. Zeng, M. Shi, F. Liu.

    Friend recommendation for cross marketing in online brand community based on intelligent attention allocation link prediction algorithm, in: Expert Systems with Applications, July 2019, vol. 139, pp. 1-11. [ DOI : 10.1016/j.eswa.2019.112839 ]

    https://hal.inria.fr/hal-02383107
  • 6N. Papanelopoulos, Y. Avrithis, S. Kollias.

    Revisiting the medial axis for planar shape decomposition, in: Computer Vision and Image Understanding, February 2019, vol. 179, pp. 66-78. [ DOI : 10.1016/j.cviu.2018.10.007 ]

    https://hal.inria.fr/hal-01930939
  • 7O. Siméoni, A. Iscen, G. Tolias, Y. Avrithis, O. Chum.

    Graph-based Particular Object Discovery, in: Machine Vision and Applications, March 2019, vol. 30, no 2, pp. 243-254. [ DOI : 10.1007/s00138-019-01005-z ]

    https://hal.inria.fr/hal-02370238

International Conferences with Proceedings

  • 8A. Antonini, F. Benatti, E. King, F. Vignale, G. Gravier.

    Modelling changes in diaries, correspondence and authors' libraries to support research on reading: the READ-IT approach, in: ODOCH 2019 - First International Workshop on Open Data and Ontologies for Cultural Heritage, Rome, Italy, June 2019, pp. 1-12.

    https://hal.archives-ouvertes.fr/hal-02130008
  • 9C. B. El Vaigh, F. Goasdoué, G. Gravier, P. Sébillot.

    Using Knowledge Base Semantics in Context-Aware Entity Linking, in: DocEng 2019 - 19th ACM Symposium on Document Engineering, Berlin, Germany, ACM, September 2019, pp. 1-10. [ DOI : 10.1007/978-3-030-27520-4_8 ]

    https://hal.inria.fr/hal-02171981
  • 10M. Gheisari, T. Furon, L. Amsaleg.

    Privacy Preserving Group Membership Verification and Identification, in: CVPR 2019 - IEEE Conference on Computer Vision and Pattern Recognition, Long Beach, United States, IEEE, June 2019, pp. 1-9, https://arxiv.org/abs/1904.10327.

    https://hal.archives-ouvertes.fr/hal-02107442
  • 11S. Gíslason, B. Þ. Jónsson, L. Amsaleg.

    Integration of Exploration and Search: A Case Study of the M3 Model, in: MMM 2019 - 25th International Conference on MultiMedia Modeling, Thessaloniki, Greece, LNCS, Springer, December 2019, vol. 11295, pp. 156-168. [ DOI : 10.1007/978-3-030-05710-7_13 ]

    https://hal.inria.fr/hal-02106893
  • 12A. Iscen, G. Tolias, Y. Avrithis, O. Chum.

    Label Propagation for Deep Semi-supervised Learning, in: CVPR 2019 - IEEE Computer Vision and Pattern Recognition Conference, Long Beach, United States, IEEE, June 2019, pp. 1-10.

    https://hal.inria.fr/hal-02370297
  • 13C. Leverger, S. Malinowski, T. Guyet, V. Lemaire, A. Bondu, A. Termier.

    Toward a Framework for Seasonal Time Series Forecasting Using Clustering, in: IDEAL 2019, Manchester, United Kingdom, October 2019, pp. 328-340. [ DOI : 10.1007/978-3-030-33607-3_36 ]

    https://hal.inria.fr/hal-02371221
  • 14Y. Lifchitz, Y. Avrithis, S. Picard, A. Bursuc.

    Dense Classification and Implanting for Few-Shot Learning, in: CVPR 2019 - IEEE Computer Vision and Pattern Recognition Conference, Long Beach, United States, IEEE, June 2019, pp. 1-10.

    https://hal.inria.fr/hal-02371279
  • 15Y. Liu, M. Shi, Q. Zhao, X. Wang.

    Point in, Box out: Beyond Counting Persons in Crowds, in: CVPR 2019 - IEEE Computer Vision and Pattern Recognition Conference, Long Beach, United States, IEEE, June 2019, pp. 1-10.

    https://hal.inria.fr/hal-02383057
  • 16H. Ragnarsdóttir, Þ. Þorleiksdóttir, O. S. Khan, B. Þ. Jónsson, G. Þ. Guðmundsson, J. Zahálka, S. Rudinac, L. Amsaleg, M. Worring.

    Exquisitor: Breaking the Interaction Barrier for Exploration of 100 Million Images, in: MM 2019 - 27th ACM International Conference on Multimedia, Nice, France, ACM, October 2019, pp. 1029-1031. [ DOI : 10.1145/3343031.3350580 ]

    https://hal.inria.fr/hal-02378272
  • 17F. C. G. Reis, R. Almeida, E. Kijak, S. Malinowski, S. J. F. Guimarães, Z. do Patrocinio.

    Combining convolutional side-outputs for road image segmentation, in: IJCNN 2019 - International Joint Conference on Neural Networks, Budapest, Hungary, IEEE, July 2019, pp. 1-8. [ DOI : 10.1109/IJCNN.2019.8851843 ]

    https://hal.inria.fr/hal-02370834
  • 18M. Shi, Z. Yang, C. Xu, Q. Chen.

    Revisiting Perspective Information for Efficient Crowd Counting, in: CVPR 2019 - IEEE Computer Vision and Pattern Recognition Conference, Long Beach, United States, IEEE, June 2019, pp. 1-10.

    https://hal.inria.fr/hal-01831109
  • 19O. Siméoni, Y. Avrithis, O. Chum.

    Local Features and Visual Words Emerge in Activations, in: CVPR 2019 - IEEE Computer Vision and Pattern Recognition Conference, Long Beach, United States, IEEE, June 2019, pp. 1-10.

    https://hal.archives-ouvertes.fr/hal-02374156
  • 20R. Souza, R. Almeida, R. Miranda, Z. Kleber Gonçalves do Patrocinio, S. Malinowski, S. J. F. Guimarães.

    BRIEF-based mid-level representations for time series classification, in: CIARP 2019 - 24th Iberoamerican Congress on Pattern Recognition, La Havane, Cuba, October 2019, pp. 449-457. [ DOI : 10.1007/978-3-030-33904-3_42 ]

    https://hal.inria.fr/hal-02371260

Conferences without Proceedings

  • 21C. Dalloux, V. Claveau, N. Grabar.

    Speculation and negation detection in french biomedical corpora, in: RANLP 2019 - Recent Advances in Natural Language Processing, Varna, Bulgaria, September 2019, pp. 1-10.

    https://hal.archives-ouvertes.fr/hal-02284444
  • 22T. Furon.

    Watermarking error exponents in the presence of noise: The case of the dual hypercone detector, in: IH&MMSEC'19 - 7th ACM Workshop on Information Hiding and Multimedia Security, Paris, France, ACM, July 2019, pp. 173-181. [ DOI : 10.1145/3335203.3335731 ]

    https://hal.archives-ouvertes.fr/hal-02122206
  • 23M. Gheisari, T. Furon, L. Amsaleg.

    Group Membership Verification with Privacy: Sparse or Dense?, in: WIFS 2019 - IEEE International Workshop on Information Forensics and Security, Delft, Netherlands, IEEE, December 2019, pp. 1-6.

    https://hal.archives-ouvertes.fr/hal-02307926
  • 24M. Gheisari, T. Furon, L. Amsaleg, B. Razeghi, S. Voloshynovskiy.

    Aggregation and embedding for group membership verification, in: ICASSP 2019 - IEEE International Conference on Acoustics, Speech and Signal Processing, Brighton, United Kingdom, IEEE, May 2019, pp. 2592-2596, https://arxiv.org/abs/1812.03943 - accepted at ICASSP 2019. [ DOI : 10.1109/ICASSP.2019.8682422 ]

    https://hal.archives-ouvertes.fr/hal-02091036
  • 25N. Grabar, C. Grouin, T. Hamon, V. Claveau.

    Annotated corpus with clinical cases in French, in: TALN 2019 - 26e Conference on Traitement Automatique des Langues Naturelles, Toulouse, France, July 2019, pp. 1-14.

    https://hal.archives-ouvertes.fr/hal-02391878
  • 26N. Grabar, C. Grouin, T. Hamon, V. Claveau.

    Information Retrieval and Information Extraction from Clinical Cases. Presentation of the DEFT 2019 Challenge, in: DEFT 2019 - Défi fouille de texte, Toulouse, France, July 2019, pp. 1-10.

    https://hal.archives-ouvertes.fr/hal-02280852
  • 27C. Grouin, N. Grabar, V. Claveau, T. Hamon.

    Clinical Case Reports for NLP, in: BioNLP 2019 - 18th ACL Workshop on Biomedical Natural Language Processing, Florence, Italy, ACL, August 2019, pp. 273–282. [ DOI : 10.18653/v1/W19-5029 ]

    https://hal.archives-ouvertes.fr/hal-02371243
  • 28A. Perquin, G. Lecorvé, D. Lolive, L. Amsaleg.

    Évaluation objective de plongements pour la synthèse de parole guidée par réseaux de neurones, in: Traitement automatique du langage naturel, Toulouse, France, July 2019.

    https://hal.archives-ouvertes.fr/hal-02419483
  • 29Y. Wang, R. Emonet, E. Fromont, S. Malinowski, E. Menager, L. Mosser, R. Tavenard.

    Classification de séries temporelles basée sur des "shapelets" interprétables par réseaux de neurones antagonistes, in: CAp 2019 - Conférence sur l'Apprentissage automatique, Toulouse, France, July 2019, pp. 1-2.

    https://hal.archives-ouvertes.fr/hal-02268004

Scientific Books (or Scientific Book chapters)

Books or Proceedings Editing

  • 34L. Amsaleg, B. Huet, M. Larson, G. Gravier, H. Hung, C.-W. Ngo, W. T. Ooi (editors)

    Proceedings of the 27th ACM International Conference on Multimedia, ACM Press, Nice, France, October 2019. [ DOI : 10.1145/3343031 ]

    https://hal.inria.fr/hal-02378803

Internal Reports

  • 35B. Caramiaux, F. Lotte, J. Geurts, G. Amato, M. Behrmann, F. Bimbot, F. Falchi, A. Garcia, J. Gibert, G. Gravier, H. Holken, H. Koenitz, S. Lefebvre, A. Liutkus, A. Perkis, R. Redondo, E. Turrin, T. Viéville, E. Vincent.

    AI in the media and creative industries, New European Media (NEM), April 2019, pp. 1-35, https://arxiv.org/abs/1905.04175.

    https://hal.inria.fr/hal-02125504

Other Publications

References in notes
  • 46L. Amsaleg, J. E. Bailey, D. Barbe, S. Erfani, M. E. Houle, V. Nguyen, M. Radovanović.

    The Vulnerability of Learning to Adversarial Perturbation Increases with Intrinsic Dimensionality, in: WIFS, 2017.
  • 47L. Amsaleg, O. Chelly, T. Furon, S. Girard, M. E. Houle, K.-I. Kawarabayashi, M. Nett.

    Estimating Local Intrinsic Dimensionality, in: KDD, 2015.
  • 48L. Amsaleg, G. Þ. Guðmundsson, B. Þ. Jónsson, M. J. Franklin.

    Prototyping a Web-Scale Multimedia Retrieval Service Using Spark, in: ACM TOMCCAP, 2018, vol. 14, no 3s.
  • 49L. Amsaleg, B. Þ. Jónsson, H. Lejsek.

    Scalability of the NV-tree: Three Experiments, in: SISAP, 2018.
  • 50R. Balu, T. Furon, L. Amsaleg.

    Sketching techniques for very large matrix factorization, in: ECIR, 2016.
  • 51S. Berrani, H. Boukadida, P. Gros.

    Constraint Satisfaction Programming for Video Summarization, in: ISM, 2013.
  • 52B. Biggio, F. Roli.

    Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning, in: Pattern Recognition, 2018.
  • 53P. Bosilj.

    Image indexing and retrieval using component trees, Université de Bretagne Sud, 2016.
  • 54X. Bost.

    A storytelling machine? : Automatic video summarization: the case of TV series, University of Avignon, France, 2016.
  • 55M. Budnik, M. Demirdelen, G. Gravier.

    A Study on Multimodal Video Hyperlinking with Visual Aggregation, in: ICME, 2018.
  • 56N. Carlini, D. A. Wagner.

    Audio Adversarial Examples: Targeted Attacks on Speech-to-Text, in: CoRR, 2018, vol. abs/1801.01944.
  • 57R. Carlini Sperandio, S. Malinowski, L. Amsaleg, R. Tavenard.

    Time Series Retrieval using DTW-Preserving Shapelets, in: SISAP, 2018.
  • 58V. Claveau, L. E. S. Oliveira, G. Bouzillé, M. Cuggia, C. M. Cabral Moro, N. Grabar.

    Numerical eligibility criteria in clinical protocols: annotation, automatic detection and interpretation, in: AIME, 2017.
  • 59A. Delvinioti, H. Jégou, L. Amsaleg, M. E. Houle.

    Image Retrieval with Reciprocal and shared Nearest Neighbors, in: VISAPP, 2014.
  • 60H. Farid.

    Photo Forensics, The MIT Press, 2016.
  • 61M. Gambhir, V. Gupta.

    Recent automatic text summarization techniques: a survey, in: Artif. Intell. Rev., 2017, vol. 47, no 1.
  • 62I. Goodfellow, Y. Bengio, A. Courville.

    Deep Learning, MIT Press, 2016.
  • 63G. Gravier, M. Ragot, L. Amsaleg, R. Bois, G. Jadi, E. Jamet, L. Monceaux, P. Sébillot.

    Shaping-Up Multimedia Analytics: Needs and Expectations of Media Professionals, in: MMM, Special Session Perspectives on Multimedia Analytics, 2016.
  • 64A. Iscen, L. Amsaleg, T. Furon.

    Scaling Group Testing Similarity Search, in: ICMR, 2016.
  • 65A. Iscen, G. Tolias, Y. Avrithis, O. Chum.

    Mining on Manifolds: Metric Learning without Labels, in: CVPR, 2018.
  • 66B. Þ. Jónsson, G. Tómasson, H. Sigurþórsson, Á. Eríksdóttir, L. Amsaleg, M. K. Larusdottir.

    A Multi-Dimensional Data Model for Personal Photo Browsing, in: MMM, 2015.
  • 67B. Þ. Jónsson, M. Worring, J. Zahálka, S. Rudinac, L. Amsaleg.

    Ten Research Questions for Scalable Multimedia Analytics, in: MMM, Special Session Perspectives on Multimedia Analytics, 2016.
  • 68H. Kim, P. Garrido, A. Tewari, W. Xu, J. Thies, N. Nießner, P. Pérez, C. Richardt, M. Zollhöfer, C. Theobalt.

    Deep Video Portraits, in: ACM TOG, 2018.
  • 69M. Laroze, R. Dambreville, C. Friguet, E. Kijak, S. Lefèvre.

    Active Learning to Assist Annotation of Aerial Images in Environmental Surveys, in: CBMI, 2018.
  • 70S. Leroux, P. Molchanov, P. Simoens, B. Dhoedt, T. Breuel, J. Kautz.

    IamNN: Iterative and Adaptive Mobile Neural Network for Efficient Image Classification, in: CoRR, 2018, vol. abs/1804.10123.
  • 71A. Lods, S. Malinowski, R. Tavenard, L. Amsaleg.

    Learning DTW-Preserving Shapelets, in: IDA, 2017.
  • 72C. Maigrot, E. Kijak, V. Claveau.

    Context-Aware Forgery Localization in Social-Media Images: A Feature-Based Approach Evaluation, in: ICIP, 2018.
  • 73D. Shahaf, C. Guestrin.

    Connecting the dots between news articles, in: KDD, 2010.
  • 74M. Shi, H. Caesar, V. Ferrari.

    Weakly Supervised Object Localization Using Things and Stuff Transfer, in: ICCV, 2017.
  • 75R. Sicre, Y. Avrithis, E. Kijak, F. Jurie.

    Unsupervised part learning for visual recognition, in: CVPR, 2017.
  • 76R. Sicre, H. Jégou.

    Memory Vectors for Particular Object Retrieval with Multiple Queries, in: ICMR, 2015.
  • 77O. Siméoni, A. Iscen, G. Tolias, Y. Avrithis, O. Chum.

    Unsupervised Object Discovery for Instance Recognition, in: WACV, 2018.
  • 78O. Siméoni, A. Iscen, G. Tolias, Y. Avrithis, O. Chum.

    Unsupervised Object Discovery for Instance Recognition, in: WACV, 2018.
  • 79H. O. Song, Y. Xiang, S. Jegelka, S. Savarese.

    Deep Metric Learning via Lifted Structured Feature Embedding, in: CVPR, 2016.
  • 80C. Tsai, M. L. Alexander, N. Okwara, J. R. Kender.

    Highly Efficient Multimedia Event Recounting from User Semantic Preferences, in: ICMR, 2014.
  • 81C. B. E. Vaigh, F. Goasdoué, G. Gravier, P. Sébillot.

    Using Knowledge Base Semantics in Context-Aware Entity Linking, in: DocEng, 2019.
  • 82O. Vinyals, A. Toshev, S. Bengio, D. Erhan.

    Show and Tell: Lessons Learned from the 2015 MSCOCO Image Captioning Challenge, in: TPAMI, 2017, vol. 39, no 4.
  • 83V. Vukotić, C. Raymond, G. Gravier.

    Bidirectional Joint Representation Learning with Symmetrical Deep Neural Networks for Multimodal and Crossmodal Applications, in: ICMR, 2016.
  • 84V. Vukotić, C. Raymond, G. Gravier.

    Generative Adversarial Networks for Multimodal Representation Learning in Video Hyperlinking, in: ICMR, 2017.
  • 85V. Vukotić.

    Deep Neural Architectures for Automatic Representation Learning from Multimedia Multimodal Data, INSA de Rennes, 2017.
  • 86J. Weston, S. Chopra, A. Bordes.

    Memory Networks, in: CoRR, 2014, vol. abs/1410.3916.
  • 87H. Yu, J. Wang, Z. Huang, Y. Yang, W. Xu.

    Video Paragraph Captioning Using Hierarchical Recurrent Neural Networks, in: CVPR, 2016.
  • 88J. Zahálka, M. Worring.

    Towards interactive, intelligent, and integrated multimedia analytics, in: VAST, 2014.
  • 89L. Zhang, M. Shi, Q. Chen.

    Crowd Counting via Scale-Adaptive Convolutional Neural Network, in: WACV, 2018.
  • 90X. Zhang, X. Zhou, M. Lin, J. Sun.

    ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices, in: CoRR, 2017, vol. abs/1707.01083.
  • 91A. da Silva Pinto, D. Moreira, A. Bharati, J. Brogan, K. W. Bowyer, P. J. Flynn, W. J. Scheirer, A. Rocha.

    Provenance filtering for multimedia phylogeny, in: ICIP, 2017.


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