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Bibliography

Publications of the year

Doctoral Dissertations and Habilitation Theses

Articles in International Peer-Reviewed Journals

  • 4R. G. Cinbis, J. Verbeek, C. Schmid.

    Approximate Fisher Kernels of non-iid Image Models for Image Categorization, in: IEEE Transactions on Pattern Analysis and Machine Intelligence, June 2016, vol. 38, no 6, pp. 1084-1098. [ DOI : 10.1109/TPAMI.2015.2484342 ]

    https://hal.inria.fr/hal-01211201
  • 5R. G. Cinbis, J. Verbeek, C. Schmid.

    Weakly Supervised Object Localization with Multi-fold Multiple Instance Learning, in: IEEE Transactions on Pattern Analysis and Machine Intelligence, January 2017, vol. 39, no 1, pp. 189-203.

    https://hal.inria.fr/hal-01123482
  • 6M. Douze, J. Revaud, J. Verbeek, H. Jégou, C. Schmid.

    Circulant temporal encoding for video retrieval and temporal alignment, in: International Journal of Computer Vision, 2016, vol. 119, no 3, pp. 291–306.

    https://hal.inria.fr/hal-01162603
  • 7V. Kalogeiton, V. Ferrari, C. Schmid.

    Analysing domain shift factors between videos and images for object detection, in: IEEE Transactions on Pattern Analysis and Machine Intelligence, April 2016. [ DOI : 10.1109/TPAMI.2016.2551239 ]

    https://hal.inria.fr/hal-01281069
  • 8A. Mishra, K. Alahari, C. Jawahar.

    Enhancing Energy Minimization Framework for Scene Text Recognition with Top-Down Cues, in: Computer Vision and Image Understanding, April 2016, vol. 145, pp. 30-42. [ DOI : 10.1016/j.cviu.2016.01.002 ]

    https://hal.inria.fr/hal-01263322
  • 9M. Paulin, J. Mairal, M. Douze, Z. Harchaoui, F. Perronnin, C. Schmid.

    Convolutional Patch Representations for Image Retrieval: an Unsupervised Approach, in: International Journal of Computer Vision, August 2016. [ DOI : 10.1007/s11263-016-0924-3 ]

    https://hal.inria.fr/hal-01277109
  • 10J. Revaud, P. Weinzaepfel, Z. Harchaoui, C. Schmid.

    DeepMatching: Hierarchical Deformable Dense Matching, in: International Journal of Computer Vision, 2016. [ DOI : 10.1007/s11263-016-0908-3 ]

    https://hal.inria.fr/hal-01148432
  • 11G. Sharma, F. Jurie, C. Schmid.

    Expanded Parts Model for Semantic Description of Humans in Still Images, in: IEEE Transactions on Pattern Analysis and Machine Intelligence, January 2017, vol. 39, no 1, pp. 87-101. [ DOI : 10.1109/TPAMI.2016.2537325 ]

    https://hal.inria.fr/hal-01199160
  • 12A. Tillmann, Y. Eldar, J. Mairal.

    DOLPHIn - Dictionary Learning for Phase Retrieval, in: IEEE Transactions on Signal Processing, December 2016, vol. 64, no 24, pp. 6485-6500, author's preprint version. [ DOI : 10.1109/TSP.2016.2607180 ]

    https://hal.inria.fr/hal-01387428
  • 13H. Wang, D. Oneata, J. Verbeek, C. Schmid.

    A robust and efficient video representation for action recognition, in: International Journal of Computer Vision, 2016, vol. 119, no 3, pp. 219–238. [ DOI : 10.1007/s11263-015-0846-5 ]

    https://hal.inria.fr/hal-01145834

Invited Conferences

International Conferences with Proceedings

  • 15B. Ham, M. Cho, C. Schmid, J. Ponce.

    Proposal Flow, in: CVPR 2016 - IEEE Conference on Computer Vision & Pattern Recognition, LAS VEGAS, United States, June 2016.

    https://hal.archives-ouvertes.fr/hal-01240281
  • 16J. Mairal.

    End-to-End Kernel Learning with Supervised Convolutional Kernel Networks, in: Advances in Neural Information Processing Systems (NIPS), Barcelona, France, December 2016.

    https://hal.inria.fr/hal-01387399
  • 17A. Mensch, J. Mairal, B. Thirion, G. Varoquaux.

    Dictionary Learning for Massive Matrix Factorization, in: International Conference on Machine Learning, New York, United States, Proceedings of the 33rd Internation Conference on Machine Learning, June 2016, vol. 48, pp. 1737–1746.

    https://hal.archives-ouvertes.fr/hal-01308934
  • 18X. Peng, C. Schmid.

    Multi-region two-stream R-CNN for action detection, in: ECCV 2016 - European Conference on Computer Vision, Amsterdam, Netherlands, Lecture Notes in Computer Science, Springer, October 2016, vol. 9908, pp. 744-759. [ DOI : 10.1007/978-3-319-46493-0_45 ]

    https://hal.inria.fr/hal-01349107
  • 19G. Rogez, C. Schmid.

    MoCap-guided Data Augmentation for 3D Pose Estimation in the Wild, in: Advances in Neural Information Processing Systems (NIPS), Barcelona, Spain, December 2016.

    https://hal.inria.fr/hal-01389486
  • 20S. Saxena, J. Verbeek.

    Convolutional Neural Fabrics, in: Advances in Neural Information Processing Systems (NIPS), Barcelona, Spain, December 2016.

    https://hal.inria.fr/hal-01359150
  • 21S. Saxena, J. Verbeek.

    Heterogeneous Face Recognition with CNNs, in: ECCV TASK-CV 2016 Workshops, Amsterdam, Netherlands, October 2016.

    https://hal.inria.fr/hal-01367455
  • 22A. Tillmann, Y. Eldar, J. Mairal.

    Dictionary learning from phaseless measurements, in: IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Shanghai, China, IEEE, March 2016, pp. 4702-4706. [ DOI : 10.1109/ICASSP.2016.7472569 ]

    https://hal.inria.fr/hal-01387416
  • 23P. Tokmakov, K. Alahari, C. Schmid.

    Weakly-Supervised Semantic Segmentation using Motion Cues, in: ECCV 2016 - European Conference on Computer Vision, Amsterdam, Netherlands, October 2016.

    https://hal.archives-ouvertes.fr/hal-01351135

Conferences without Proceedings

  • 24P. Luc, C. Couprie, S. Chintala, J. Verbeek.

    Semantic Segmentation using Adversarial Networks, in: NIPS Workshop on Adversarial Training, Barcelona, Spain, December 2016.

    https://hal.inria.fr/hal-01398049
  • 25A. Mensch, J. Mairal, G. Varoquaux, B. Thirion.

    Subsampled online matrix factorization with convergence guarantees, in: NIPS Workshop on Optimization for Machine Learning, Barcelone, Spain, December 2016.

    https://hal.archives-ouvertes.fr/hal-01405058

Other Publications

  • 26A. Bietti, J. Mairal.

    Stochastic Optimization with Variance Reduction for Infinite Datasets with Finite-Sum Structure, October 2016, working paper; a short version has been accepted to the NIPS OPT2016 workshop.

    https://hal.inria.fr/hal-01375816
  • 27G. Hu, X. Peng, Y. Yang, T. Hospedales, J. Verbeek.

    Frankenstein: Learning Deep Face Representations using Small Data, April 2016, working paper or preprint.

    https://hal.inria.fr/hal-01306168
  • 28H. Lin, J. Mairal, Z. Harchaoui.

    QuickeNing: A Generic Quasi-Newton Algorithm for Faster Gradient-Based Optimization, October 2016, working paper; a short version has been accepted to the NIPS workshop on optimization for machine learning 2016.

    https://hal.inria.fr/hal-01376079
  • 29M. Pedersoli, T. Lucas, C. Schmid, J. Verbeek.

    Areas of Attention for Image Captioning, November 2016, working paper or preprint.

    https://hal.inria.fr/hal-01428963
  • 30P. Tokmakov, K. Alahari, C. Schmid.

    Learning Semantic Segmentation with Weakly-Annotated Videos, July 2016, working paper or preprint.

    https://hal.inria.fr/hal-01292794
  • 31P. Tokmakov, K. Alahari, C. Schmid.

    Learning Motion Patterns in Videos, January 2017, working paper or preprint.

    https://hal.archives-ouvertes.fr/hal-01427480
  • 32G. Varol, I. Laptev, C. Schmid.

    Long-term Temporal Convolutions for Action Recognition, April 2016, working paper or preprint.

    https://hal.inria.fr/hal-01241518
  • 33P. Weinzaepfel, X. MARTIN, C. Schmid.

    Towards Weakly-Supervised Action Localization, May 2016, working paper or preprint.

    https://hal.inria.fr/hal-01317558


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