Detailed publication index
2023
Conference articles
-
Elliot Chane-Sane,
Cordelia Schmid,
and Ivan Laptev.
Learning Video-Conditioned Policies for Unseen Manipulation Tasks.
In ICRA,
2023.
-
Antoine Yang,
Arsha Nagrani,
Ivan Laptev,
Josef Sivic,
and Cordelia Schmid.
VidChapters-7M: Video Chapters at Scale.
In NeurIPS,
2023.
-
Antoine Yang,
Arsha Nagrani,
Paul Hongsuck Seo,
Antoine Miech,
Jordi Pont-Tuset,
Ivan Laptev,
Josef Sivic,
and Cordelia Schmid.
Vid2Seq: Large-Scale Pretraining of a Visual Language Model for Dense Video Captioning.
In CVPR,
2023.
2022
Articles in journal or book chapters
-
A. Yang,
A. Miech,
J. Sivic,
I. Laptev,
and C. Schmid.
Learning to Answer Visual Questions from Web Videos.
TPAMI,
2022.
Conference articles
-
S. Chen,
P.-L. Guhur,
M. Tapaswi,
C. Schmid,
and I. Laptev.
Think Global, Act Local: Dual-scale Graph Transformer for Vision-and-Language Navigation.
In IEEE Conference on Computer Vision and Pattern Recognition,
2022.
-
L. Montaut,
Q. Le Lidec,
V. Petrik,
J. Sivic,
and J. Carpentier.
Collision Detection Accelerated: An Optimization Perspective.
In RSS,
2022.
-
T. Soucek,
J.-B. Alayrac,
A. Miech,
I. Laptev,
and J. Sivic.
Look for the Change: Learning Object States and State-Modifying Actions From Untrimmed Web Videos.
In IEEE Conference on Computer Vision and Pattern Recognition,
2022.
-
A. Yang,
A. Miech,
J. Sivic,
I. Laptev,
and C. Schmid.
TubeDETR: Spatio-Temporal Video Grounding with Transformers.
In IEEE Conference on Computer Vision and Pattern Recognition,
2022.
-
A. Yang,
A. Miech,
J. Sivic,
I. Laptev,
and C. Schmid.
Zero-Shot Video Question Answering via Frozen Bidirectional Language Models.
In NeurIPS,
2022.
2021
Articles in journal or book chapters
-
Q. Le Lidec,
I. Kalevatykh,
I. Laptev,
C. Schmid,
and J. Carpentier.
Differentiable simulation for physical system identification.
IEEE Robotics and Automation Letters,
2021.
-
G. Varol,
I. Laptev,
C. Schmid,
and A. Zisserman.
Synthetic Humans for Action Recognition from Unseen Viewpoints.
International Journal of Computer Vision,
2021.
Conference articles
-
E. Chane-Sane,
C. Schmid,
and I. Laptev.
Goal-Conditioned Reinforcement Learning with Imagined Subgoals.
In ICML,
2021.
-
S. Chen,
P.-L. Guhur,
C. Schmid,
and I. Laptev.
History Aware Multimodal Transformer for Vision-and-Language Navigation.
In NeurIPS,
2021.
-
T. Chu,
X. Li,
H. V. Vo,
R. M. Summers,
and E. Sizikova.
Improving Weakly Supervised Lesion Segmentation Using Multi-Task Learning.
In MIDL,
2021.
-
Y. Labbé,
J. Carpentier,
M. Aubry,
and J. Sivic.
Single-view robot pose and joint angle estimation via render & compare.
In IEEE Conference on Computer Vision and Pattern Recognition,
2021.
-
Q. Le Lidec,
I. Laptev,
C. Schmid,
and J. Carpentier.
Differentiable rendering with perturbed optimizers.
In NeurIPS,
2021.
-
G. Le Moing,
J. Ponce,
and C. Schmid.
CCVS: Context-aware Controllable Video Synthesis.
In NeurIPS,
2021.
-
T. Monnier,
E. Vincent,
J. Ponce,
and M. Aubry.
Unsupervised Layered Image Decomposition into Object Prototypes.
In International Conference on Computer Vision,
2021.
-
O. Siméoni,
G. Puy,
H. V. Vo,
S. Roburin,
S. Gidaris,
A. Bursuc,
P. Pérez,
R. Marlet,
and J. Ponce.
Localizing Objects with Self-Supervised Transformers and no Labels.
In ,
2021.
-
H. V. Vo,
E. Sizikova,
C. Schmid,
P. Perez,
and J. Ponce.
Large-Scale Unsupervised Object Discovery.
In NeurIPS,
2021.
-
A. Yang,
A. Miech,
J. Sivic,
I. Laptev,
and C. Schmid.
Just Ask: Learning to Answer Questions from Millions of Narrated Videos.
In International Conference on Computer Vision,
2021.
2020
Articles in journal or book chapters
-
Kim B.,
Ponce J.,
and Ham B..
Deformable Kernel Networks for Joint Image Filtering.
Accepted for publication in the International Journal of Computer Vision,
2020.
-
Lee J.,
Kim D.,
Lee W.,
Ponce J.,
and Ham B..
Learning Semantic Correspondence Exploiting an Object-level Prior.
IEEE Transactions on Pattern Analysis and Machine Intelligence,
2020.
-
Y. Labbé,
S. Zagoruyko,
I. Kalevatykh,
I. Laptev,
J. Carpentier,
M. Aubry,
and J. Sivic.
Monte-Carlo Tree Search for Efficient Visually Guided Rearrangement Planning.
IEEE Robotics and Automation Letters,
2020.
-
Robin Strudel,
Ricardo Garcia,
Justin Carpentier,
Jean-Paul Laumond,
Ivan Laptev,
and Cordelia Schmid.
Learning Obstacle Representations for Neural Motion Planning.
arXiv:2008.11174,
2020.
Conference articles
-
Achal Dave,
Tarasha Khurana,
Pavel Tokmakov,
Cordelia Schmid,
and Deva Ramanan.
TAO: A Large-Scale Benchmark for Tracking Any Object.
In European Conference on Computer Vision,
2020.
-
Y. Ding,
J. Yang,
J. Ponce,
and H. Kong.
Minimal Solutions to Relative Pose Estimation From Two Views Sharing aCommon Direction With Unknown Focal Length.
In IEEE Conference on Computer Vision and Pattern Recognition,
2020.
-
Hazel Doughty,
Ivan Laptev,
Walterio Mayol-Cuevas,
and Dima Damen.
Action Modifiers: Learning from Adverbs in Instructional Videos.
In IEEE Conference on Computer Vision and Pattern Recognition,
2020.
-
Nikita Dvornik,
Cordelia Schmid,
and Julien Mairal.
Selecting Relevant Features from a Multi-domain Representation for Few-shot Classification.
In European Conference on Computer Vision (ECCV),
2020.
-
Yana Hasson,
Bugra Tekin,
Federica Bogo,
Ivan Laptev,
Marc Pollefeys,
and Cordelia Schmid.
Leveraging Photometric Consistency over Time for Sparsely Supervised Hand-Object Reconstruction.
In IEEE Conference on Computer Vision and Pattern Recognition,
2020.
-
Min J.,
Lee J.,
Ponce J.,
and Cho M..
Learning to Compose Hypercolumns for Visual Correspondence.
In European Conference on Computer Vision,
2020.
-
Anna Kukleva,
Makarand Tapaswi,
and Ivan Laptev.
Learning Interactions and Relationships between Movie Characters.
In IEEE Conference on Computer Vision and Pattern Recognition,
2020.
-
Y. Labbé,
J. Carpentier,
M. Aubry,
and J. Sivic.
CosyPose: Consistent multi-view multi-object 6D pose estimation.
In European Conference on Computer Vision,
2020.
-
Bruno Lecouat,
Jean Ponce,
and Julien Mairal.
Designing and Learning Trainable Priors with Non-Cooperative Games.
In Advances in Neural Information Processing Systems,
2020.
-
Bruno Lecouat,
Jean Ponce,
and Julien Mairal.
Fully Trainable and Interpretable Non-Local Sparse Models for Image Restoration.
In European Conference on Computer Vision,
2020.
-
Antoine Miech,
Jean-Baptiste Alayrac,
Lucas Smaira,
Ivan Laptev,
Josef Sivic,
and Andrew Zisserman.
End-to-end learning of visual representations from uncurated instructional videos.
In IEEE Conference on Computer Vision and Pattern Recognition,
2020.
-
Alexander Pashevich,
Igor Kalevatykh,
Ivan Laptev,
and Cordelia Schmid.
Learning visual policies for building 3D shape categories.
In International Conference on Intelligent Robots and Systems,
2020.
-
Ignacio Rocco,
Relja Arandjelovic,
and Josef Sivic.
Efficient Neighbourhood Consensus Networks via Submanifold Sparse Convolutions.
In European Conference on Computer Vision,
2020.
-
Alexandre Sablayrolles,
Matthijs Douze,
Cordelia Schmid,
and Hervé Jégou.
Radioactive data: tracing through training.
In International Conference on Machine Learning,
2020.
-
Vivek Sharma,
Makarand Tapaswi,
Saquib Sarfraz,
and Rainer Stiefelhagen.
Clustering based Contrastive Learning for Improving Face Representations.
In IEEE International Conference on Automatic Face and Gesture Recognition (FG),
2020.
-
Robin Strudel,
Alexander Pashevich,
Igor Kalevatykh,
Ivan Laptev,
Josef Sivic,
and Cordelia Schmid.
Learning to combine primitive skills: A step towards versatile robotic manipulation.
In International Conference on Robotics and Automation,
2020.
-
Eboli T.,
Sun J.,
and Ponce J..
End-to-end Interpretable Learning of Non-blind Image Deblurring.
In European Conference on Computer Vision,
2020.
-
Huy V. Vo,
Patrick Pérez,
and Jean Ponce.
Toward unsupervised, multi-object discovery in large-scale image collections.
In European Conference on Computer Vision,
2020.
-
D. Zhukov,
J.-B. Alayrac,
I. Laptev,
and J. Sivic.
Learning Actionness via Long-range Temporal Order Verification.
In European Conference on Computer Vision,
2020.
2019
Thesis
-
Gül Varol.
Learning Human Body and Human Action Representations from Visual Data.
PhD thesis,
ENS,
2019.
Articles in journal or book chapters
-
J. Min,
J. Lee,
J. Ponce,
and M. Cho.
SPair-71k: A Large-scale Benchmark for Semantic Correspondence.
arXiv e-prints,
pp arXiv:1908.10543,
August 2019.
-
B. Osserman and M. Trager.
Multigraded Cayley-Chow forms.
Advances in Mathematics,
348:583-606,
2019.
Conference articles
-
Y. Ding,
J. Yang,
J. Ponce,
and H. Kong.
An Efficient Solution to the Homography-Based Relative Pose Problem With a Common Reference Direction.
In International Conference on Computer Vision,
2019.
-
M. Dusmanu,
I. Rocco,
T. Pajdla,
M. Pollefeys,
J. Sivic,
A. Torii,
and T. Sattler.
D2-Net: A Trainable CNN for Joint Detection and Description of Local Features.
In IEEE Conference on Computer Vision and Pattern Recognition,
2019.
-
Y. Hasson,
G. Varol,
D. Tzionas,
I. Kalevatykh,
M. J. Black,
I. Laptev,
and C. Schmid.
Learning joint reconstruction of hands and manipulated objects.
In IEEE Conference on Computer Vision and Pattern Recognition,
2019.
-
J. Lee,
D. Kim,
J. Ponce,
and B. Ham.
SFNet: Learning Object-aware Semantic Correspondence.
In IEEE Conference on Computer Vision and Pattern Recognition,
2019.
-
Z. Li,
J. Sedlar,
J. Carpentier,
I. Laptev,
N. Mansard,
and J. Sivic.
Estimating 3D Motion and Forces of Person-Object Interactions from Monocular Video.
In IEEE Conference on Computer Vision and Pattern Recognition,
2019.
-
Antoine Miech,
Dimitri Zhukov,
Jean-Baptiste Alayrac,
Makarand Tapaswi,
Ivan Laptev,
and Josef Sivic.
HowTo100M: Learning a Text-Video Embedding by Watching Hundred Million Narrated Video Clips.
In International Conference on Computer Vision,
2019.
-
J. Min,
J. Lee,
J. Ponce,
and M. Cho.
Hyperpixel Flow: Semantic Correspondence with Multi-layer Neural Features.
In International Conference on Computer Vision,
2019.
-
Alexander Pashevich,
Robin Strudel,
Igor Kalevatykh,
Ivan Laptev,
and Cordelia Schmid.
Learning to Augment Synthetic Images for Sim2Real Policy Transfer.
In International Conference on Intelligent Robots and Systems,
2019.
-
Makarand Tapaswi,
Marc T. Law,
and Sanja Fidler.
Video Face Clustering with Unknown Number of Clusters.
In International Conference on Computer Vision,
2019.
-
M. Trager,
M. Hebert,
and J. Ponce.
Coordinate-Free Carlsson-Weinshall Duality and Relative Multi-View Geometry.
In IEEE Conference on Computer Vision and Pattern Recognition,
2019.
-
H. V. Vo,
F. Bach,
M. Cho,
K. Han,
Y. LeCun,
P. Pérez,
and J. Ponce.
Unsupervised Image Matching and Object Discovery as Optimization.
In IEEE Conference on Computer Vision and Pattern Recognition,
2019.
-
Y. Zhang,
Y. Gao,
S. Gu,
Y. Guo,
M. Liu,
Z. Sun,
Z. Hou,
H. Yang,
Y. Wang,
J. Yang,
J. Ponce,
and H. Kong.
Build your own hybrid thermal/EO camera for autonomous vehicle.
In to appear in the Proc. of the IEEE International Conference on Robotics and Automation,
2019.
-
D. Zhukov,
J.-B. Alayrac,
R.G. Cinbis,
D. Fouhey,
I. Laptev,
and J. Sivic.
Cross-task weakly supervised learning from instructional videos.
In IEEE Conference on Computer Vision and Pattern Recognition,
2019.
2018
Thesis
-
Jean-Baptiste Alayrac.
Structured Learning from Videos and Language.
PhD thesis,
ENS,
2018.
-
Guilhem Chéron.
Structured modeling and recognition of human actions in video.
PhD thesis,
ENS,
2018.
-
Maxime Oquab.
Convolutional neural networks: towards less supervision for visual recognition.
PhD thesis,
ENS,
2018.
-
Matthew Trager.
Cameras, Shapes, and Contours: Geometric Models in Computer Vision.
PhD thesis,
ENS,
2018.
-
Tuan-Hung Vu.
Learning visual models for person detection and action prediction.
PhD thesis,
ENS,
2018.
Articles in journal or book chapters
-
J.-B. Alayrac,
P. Bojanowski,
N. Agrawal,
I. Laptev,
J. Sivic,
and S. Lacoste-Julien.
Learning from Narrated Instruction Videos.
IEEE Transactions on Pattern Analysis and Machine Intelligence,
40(9):2194-2208,
2018.
-
B. Ham,
M. Cho,
and J. Ponce.
Robust Guided Image Filtering Using Nonconvex Potentials.
IEEE Transactions on Pattern Analysis and Machine Intelligence,
40(1):192-207,
2018.
-
B. Ham,
M. Cho,
C. Schmid,
and J. Ponce.
Proposal Flow: Semantic Correspondences from Object Proposals.
IEEE Transactions on Pattern Analysis and Machine Intelligence,
40(7):1711-1725,
2018.
-
K. Kohn,
B. Sturmfels,
and M. Trager.
Changing Views on Curves and Surfaces.
Acta Mathematica Vietnamica,
43(1):1-29,
2018.
-
I. Rocco,
R. Arandjelovic,
and J. Sivic.
Convolutional neural network architecture for geometric matching.
IEEE Transactions on Pattern Analysis and Machine Intelligence,
2018.
-
G. Varol,
I. Laptev,
and C. Schmid.
Long-term Temporal Convolutions for Action Recognition.
IEEE Transactions on Pattern Analysis and Machine Intelligence,
40(6):1510-1517,
2018.
-
Y. Zhang,
S. Yingna,
J. Yang,
J. Ponce,
and H. Kong.
When Dijkstra meets vanishing point: a stereo vision approach for road detection.
IEEE Transactions on Image Processing,
2018.
Conference articles
-
L. Bottou,
M. Arjovsky,
D. Lopez-Paz,
and M Oquab.
Geometrical Insights for Implicit Generative Modeling.
In Braverman Readings in Machine Learning. Key Ideas from Inception to Current State,
2018.
-
B. Bukh,
X. Goaoc,
A. Hubard,
and M. Trager.
Consistent Sets of Lines with no Colorful Incidence.
In SoCG 2018 - 34th International Symposium on Computational Geometry,
2018.
-
G. Chéron,
J.-B. Alayrac,
I. Laptev,
and C. Schmid.
A Flexible Model for Training Action Localization with Varying Levels of Supervision.
In Advances in Neural Information Processing Systems,
2018.
-
E. Oyallon,
E. Belilovsky,
S. Zagoruyko,
and M. Valko.
Compressing the Input for CNNs with the First-Order Scattering Transform.
In European Conference on Computer Vision,
2018.
-
I. Rocco,
R. Arandjelovic,
and J. Sivic.
End-to-end weakly-supervised semantic alignment.
In IEEE Conference on Computer Vision and Pattern Recognition,
2018.
-
I. Rocco,
M. Cimpoi,
R. Arandjelovic,
A. Torii,
T. Pajdla,
and J. Sivic.
Neighbourhood Consensus Networks.
In Advances in Neural Information Processing Systems,
2018.
-
T. Sattler,
W. Maddern,
C. Toft,
A. Torii,
L. Hammarstrand,
E. Stenborg,
D. Safari,
M. Okutomi,
M. Pollefeys,
J. Sivic,
F. Kahl,
and T. Pajdla.
Benchmarking 6DOF Outdoor Visual Localization in Changing Conditions.
In IEEE Conference on Computer Vision and Pattern Recognition,
2018.
-
H. Taira,
M. Okutomi,
T. Sattler,
M. Cimpoi,
M. Pollefeys,
J. Sivic,
T. Pajdla,
and A. Torii.
InLoc: Indoor Visual Localization with Dense Matching and View Synthesis.
In IEEE Conference on Computer Vision and Pattern Recognition,
2018.
-
M. Trager,
B. Osserman,
and J. Ponce.
On the Solvability of Viewing Graphs.
In European Conference on Computer Vision,
2018.
-
G. Varol,
D. Ceylan,
B. Russell,
J. Yang,
E. Yumer,
I. Laptev,
and C. Schmid.
BodyNet: Volumetric Inference of 3D Human Body Shapes.
In European Conference on Computer Vision,
2018.
Internal reports
-
T. Eboli,
J. Sun,
and J. Ponce.
Neural Embedding of an Iterative Deconvolution Algorithm for Motion blur Estimation and Removal.
Technical report,
2018.
-
M. Trager and J. Ponce.
In Defense of Relative Multi-View Geometry.
Technical report,
2018.
2017
Thesis
-
Rafael Sampaio de Rezende.
New methods for image classification, image retrieval and semantic correspondence.
PhD thesis,
ENS,
2017.
Articles in journal or book chapters
-
H. Idrees,
A. R. Zamir,
Y.-G. Jiang,
A. Gorban,
I. Laptev,
R. Sukthankar,
and M. Shah.
The THUMOS challenge on action recognition for videos ''in the wild''.
Computer Vision and Image Understanding,
155:1-23,
2017.
-
J. Ponce,
B. Sturmfels,
and M. Trager.
Congruences and Concurrent Lines in Multi-View Geometry.
Advances in Applied Mathematics,
88:62-91,
2017.
Conference articles
-
J.-B. Alayrac,
J. Sivic,
I. Laptev,
and S. Lacoste-Julien.
Joint Discovery of Object States and Manipulation Actions.
In International Conference on Computer Vision,
2017.
-
K. Han,
R. Rezende,
B. Ham,
K. K. Wong,
M. Cho,
C. Schmid,
and J. Ponce.
SCNet: Learning Semantic Correspondence.
In International Conference on Computer Vision,
2017.
-
D. Lopez-Paz and M. Oquab.
Revisiting Classifier Two-Sample Tests.
In International Conference on Learning Representations,
2017.
-
A. Miech,
J.-B. Alayrac,
P. Bojanowski,
I. Laptev,
and J. Sivic.
Learning from Video and Text via Large-Scale Discriminative Clustering.
In International Conference on Computer Vision,
2017.
-
A. Osokin,
A. Chessel,
R. E. Carazo Salas,
and F. Vaggi.
GANs for Biological Image Synthesis.
In International Conference on Computer Vision,
2017.
-
J. Peyre,
I. Laptev,
C. Schmid,
and J. Sivic.
Weakly-supervised learning of visual relations.
In International Conference on Computer Vision,
2017.
-
R. Rezende,
J. Zepeda,
J. Ponce,
F. Bach,
and P. Pérez.
Kernel Square-Loss Exemplar Machines for Image Retrieval.
In IEEE Conference on Computer Vision and Pattern Recognition,
2017.
-
I. Rocco,
R. Arandjelovic,
and J. Sivic.
Convolutional neural network architecture for geometric matching.
In IEEE Conference on Computer Vision and Pattern Recognition,
2017.
-
M. Trager,
B. Sturmfels,
J. Canny,
M. Hebert,
and J. Ponce.
General models for rational cameras and the case of two-slit projections.
In IEEE Conference on Computer Vision and Pattern Recognition,
2017.
-
G. Varol,
J. Romero,
X. Martin,
N. Mahmood,
M. J. Black,
I. Laptev,
and C. Schmid.
Learning from Synthetic Humans.
In IEEE Conference on Computer Vision and Pattern Recognition,
2017.
2016
Thesis
-
Piotr Bojanowski.
Learning to annotate dynamic video scenes.
PhD thesis,
ENS,
2016.
-
Guillaume Seguin.
Person analysis in stereoscopic movies.
PhD thesis,
ENS,
2016.
Articles in journal or book chapters
-
J. Sun and J. Ponce.
Learning Dictionary of Discriminative Part Detectors for Image Categorization and Cosegmentation.
International Journal of Computer Vision,
120(2):111-133,
2016.
-
M. Trager,
M. Hebert,
and J. Ponce.
Trinocular Geometry Revisited.
International Journal of Computer Vision,
120(2):134-152,
2016.
Conference articles
-
J.-B. Alayrac,
P. Bojanowski,
N. Agrawal,
I. Laptev,
J. Sivic,
and S. Lacoste-Julien.
Unsupervised Learning from Narrated Instruction Videos.
In IEEE Conference on Computer Vision and Pattern Recognition,
2016.
-
R. Arandjelovic,
P. Gronat,
A. Torii,
T. Pajdla,
and J. Sivic.
NetVLAD: CNN architecture for weakly supervised place recognition.
In IEEE Conference on Computer Vision and Pattern Recognition,
2016.
-
B. Ham,
M. Cho,
Schmid. C,
and J. Ponce.
Proposal Flow.
In IEEE Conference on Computer Vision and Pattern Recognition,
2016.
-
V. Kantorov,
M. Oquab,
M. Cho,
and I. Laptev.
ContextLocNet: Context-aware Deep Network Models for Weakly Supervised Localization.
In European Conference on Computer Vision,
2016.
-
S. Kwak,
M. Cho,
and I. Laptev.
Thin-Slicing for Pose: Learning to Understand Pose without Explicit Pose Estimation.
In IEEE Conference on Computer Vision and Pattern Recognition,
2016.
-
G. Seguin,
P. Bojanowski,
R. Lajugie,
and I. Laptev.
Instance-level video segmentation from object tracks.
In IEEE Conference on Computer Vision and Pattern Recognition,
2016.
-
G. A. Sigurdsson,
G. Varol,
X. Wang,
I. Laptev,
A. Farhadi,
and A. Gupta.
Hollywood in Homes: Crowdsourcing Data Collection for Activity Understanding.
In European Conference on Computer Vision,
2016.
-
M. Trager,
M. Hebert,
and J. Ponce.
Consistency of Silhouettes and Their Duals.
In IEEE Conference on Computer Vision and Pattern Recognition,
2016.
-
Y. Zhong,
R. Arandjelovic,
and A. Zisserman.
Faces In Places: Compound query retrieval.
In British Machine Vision Conference,
2016.
Internal reports
-
A. Babenko,
R. Arandjelovic,
and V. Lempitsky.
Pairwise Quantization.
Technical report,
2016.
2015
Thesis
-
Mathieu Aubry.
Representing 3D models for alignment and recognition.
PhD thesis,
ENS,
2015.
-
Vincent Delaitre.
Modeling and Recognizing Interactions between People, Objects and Scenes.
PhD thesis,
ENS,
2015.
Articles in journal or book chapters
-
M. Aubry,
B. Russell,
and J. Sivic.
Visual Analysis and Geolocalization of Large-Scale Imagery,
chapter Visual geo-localization of non-photographic depictions via 2D-3D alignment.
Springer,
2015.
-
G. Seguin,
K. Alahari,
J. Sivic,
and I. Laptev.
Pose Estimation and Segmentation of Multiple People in Stereoscopic Movies.
IEEE Transactions on Pattern Analysis and Machine Intelligence,
37(8):1643-1655,
2015.
-
A. Torii,
J. Sivic,
T. Pajdla,
and M. Okutomi.
Visual place recognition with repetitive structures.
IEEE Transactions on Pattern Analysis and Machine Intelligence,
37(11):2346-2359,
2015.
Conference articles
-
P. Bojanowski,
R. Lajugie,
E. Grave,
F. Bach,
I. Laptev,
J. Ponce,
and C. Schmid.
Weakly-Supervised Alignment of Video With Text.
In International Conference on Computer Vision,
2015.
-
V. Chari,
S. Lacoste-Julien,
I. Laptev,
and J. Sivic.
On Pairwise Costs for Network Flow Multi-Object Tracking.
In IEEE Conference on Computer Vision and Pattern Recognition,
2015.
-
G. Cheron,
I. Laptev,
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M. Aubry,
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2014.
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J. Mairal,
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2012
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Learning hierarchical feature extractors for image recognition.
PhD thesis,
New York University,
2012.
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Non-rigid image alignment for object recognition.
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2012.
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Supervised Statistical Representations for Human Action Recognition in Video.
PhD thesis,
Université de Rennes 1,
2012.
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Removing Camera Shake Blur and Unwanted Occluders from Photographs.
PhD thesis,
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ACM Transactions on Graphics (SIGGRAPH),
31(4):101:1-101:9,
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IEEE Transactions on Pattern Analysis and Machine Intelligence,
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International Journal of Computer Vision,
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In European Conference on Computer Vision,
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PAC-Bayesian aggregation and multi-armed bandits.
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Universite Paris Est, France,
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Low-Rank Optimization on the Cone of Positive Semidefinite Matrices.
SIAM Journal on Optimization,
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Infinite Images: Creating and Exploring a Large Photorealistic Virtual Space.
Proceedings of the IEEE,
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IEEE Transactions on Image Processing,
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Online Learning for Matrix Factorization and Sparse Coding.
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Taking the Bite out of Automated Naming of Characters in TV Video.
Image and Video Computing,
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International Journal of Computer Vision,
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High-Fidelity Image-Based Modeling.
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J. Mairal,
G. Sapiro,
and Michael Elad.
Learning multiscale sparse representations for image and video restoration.
SIAM Multiscale Modeling and Simulation,
7(1):214-241,
April 2008.
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A. Rakotomamonjy,
F. Bach,
S. Canu,
and Y. Grandvalet.
SimpleMKL.
Journal of Machine Learning Research,
9:2491-2521,
2008.
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J. Sivic and A. Zisserman.
Efficient Visual Search for Objects in Videos.
Proceedings of the IEEE,
96(4):548-566,
2008.
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A. d'Aspremont,
F. Bach,
and L. El Ghaoui.
Optimal solutions for sparse principal component analysis.
Journal of Machine Learning Research,
9:1269-1294,
2008.
Conference articles
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C. Archambeau and F. Bach.
Sparse probabilistic projections.
In Advances in Neural Information Processing Systems,
2008.
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F. Bach.
Bolasso: Model consistent Lasso estimation through the bootstrap.
In International Conference on Machine Learning,
2008.
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F. Bach.
Graph kernels between point clouds.
In International Conference on Machine Learning,
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O. Duchenne,
J.-Y. Audibert,
R. Keriven,
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and F. Segonne.
Segmentation by transduction.
In IEEE Conference on Computer Vision and Pattern Recognition,
2008.
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Y. Furukawa and J. Ponce.
Accurate camera calibration from multi-view stereo and bundle adjustment.
In IEEE Conference on Computer Vision and Pattern Recognition,
2008.
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Y. Furukawa and J. Ponce.
Dense 3D motion capture from synchronized video streams..
In IEEE Conference on Computer Vision and Pattern Recognition,
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Z. Harchaoui,
F. Bach,
and E. Moulines.
Kernel change-point analysis.
In Advances in Neural Information Processing Systems,
2008.
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C. Liu,
J. Yuen,
A. Torralba,
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and W. T. Freeman.
SIFT Flow: Dense Correspondence across Different Scenes.
In European Conference on Computer Vision,
2008.
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J. Mairal,
F. Bach,
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Discriminative Learned Dictionaries for Local Image Analysis.
In IEEE Conference on Computer Vision and Pattern Recognition,
2008.
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J. Mairal,
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Supervised Dictionary Learning.
In Advances in Neural Information Processing Systems,
2008.
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J. Mairal,
Michael Elad,
and G. Sapiro.
Sparse Learned Representations for Image Restoration.
In 4th World conference of the IASC (International Association for Statistical Computing),
2008.
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J. Mairal,
Marius Leordeanu,
F. Bach,
Martial Hebert,
and J. Ponce.
Discriminative Sparse Image Models for Class-Specific Edge Detection and Image Interpretation.
In European Conference on Computer Vision,
2008.
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V. Mnih,
Cs. Szepesvári,
and J.-Y. Audibert.
Empirical Bernstein stopping.
In International Conference on Machine Learning,
2008.
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James Philbin,
Ondrej Chum,
Michael Isard,
J. Sivic,
and A. Zisserman.
Lost in Quantization: Improving Particular Object Retrieval in Large Scale Image Databases.
In IEEE Conference on Computer Vision and Pattern Recognition,
2008.
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James Philbin,
J. Sivic,
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Geometric LDA: A Generative Model for Particular Object Discovery.
In British Machine Vision Conference,
2008.
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H. Sahbi,
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Context-Dependent Kernel Design for Object Matching and Recognition.
In IEEE Conference on Computer Vision and Pattern Recognition,
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H. Sahbi,
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Manifold Learning using Robust Graph Laplacian for Interactive Image Retrieval.
In IEEE Conference on Computer Vision and Pattern Recognition,
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J. Sivic,
Biliana Kaneva,
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2008.
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J. Sivic,
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In IEEE Conference on Computer Vision and Pattern Recognition,
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F. Bach,
J. Mairal,
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Convex Sparse Matrix Factorizations.
Technical report,
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Note: ArXiv:0812.1869.
2007
Books and proceedings
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J. Ponce,
M. Hebert,
C. Schmid,
and A. Zisserman.
Toward Category-Level Object Recognition,
volume 4170.
Springer-Verlag Lecture Notes in Computer Science,
2007.
Articles in journal or book chapters
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J.-Y Audibert and O. Bousquet.
Combining PAC-Bayesian and generic chaining bounds.
Journal of Machine Learning Research,
8:863-889,
2007.
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J.-Y. Audibert and A. Tsybakov.
Fast learning rates for plug-in classifiers.
Annals of Statistics,
35(2):608-633,
2007.
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G. Charpiat,
P. Maurel,
J.-P. Pons,
R. Keriven,
and O. Faugeras.
Generalized gradients: Priors on minimization flows.
The International Journal of Computer Vision,
73(3):325-344,
July 2007.
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J. Erickson,
S. Thite,
F. Rothganger,
and J. Ponce.
Capturing a Convex Object with Three Discs.
IEEE Trans. Robotics and Automation,
6(23):1133-1140,
2007.
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S. Har-Peled and A. Kushal.
Smaller Coresets for k-Median and k-Means Clustering.
Discrete and Computational Geometry,
37(1):3-19,
2007.
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M. Hein,
J.-Y. Audibert,
and U. Von Luxburg.
Graph laplacians and their convergence on random neighborhood graphs.
Journal of Machine Learning Research,
8:1325-1368,
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S. Lazebnik,
Y. Furukawa,
and J. Ponce.
Projective Visual Hulls.
International Journal of Computer Vision,
74(2):137-165,
2007.
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J.-P. Pons and J.-D. Boissonnat.
A Lagrangian approach to dynamic interfaces through kinetic triangulation of the ambient space.
Computer Graphics Forum,
26(2):227-239,
2007.
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J.-P. Pons,
R. Keriven,
and O. Faugeras.
Multi-view stereo reconstruction and scene flow estimation with a global image-based matching score.
The International Journal of Computer Vision,
72(2):179-193,
April 2007.
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F. Rothganger,
S. Lazebnik,
C. Schmid,
and J. Ponce.
Segmenting, Modeling, and Matching Video Clips Containing Multiple Moving Objects.
IEEE Transactions on Pattern Analysis and Machine Intelligence,
29(3):477-491,
2007.
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F. Segonne,
J. Pacheco,
and B. Fischl.
Geometrically-Accurate Topology Simplification of Triangulated Cortical Surfaces Using Non-Separating Loops.
IEEE Transaction on Medical Imaging,
26(4):518-529,
April 2007.
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F. Ségonne.
Active Contours Under Topology Control - Genus Preserving Level Sets.
International Journal of Computer Vision,
2007.
Note: To appear.
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P. Yu,
P. Ellen Grant,
Y. Qi,
X. Han,
F. Ségonne,
R. Pienaar,
E. Busa,
J. Pacheco,
N. Makris,
R.-L Buckner,
P. Golland,
and B. Fischl.
Cortical surface shape analysis based on spherical wavelets.
IEEE Transaction on Medical Imaging,
26(4):582-597,
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Conference articles
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E. Aganj,
J.-P. Pons,
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and R. Keriven.
Spatio-temporal shape from silhouette using four-dimensional Delaunay meshing.
In IEEE International Conference on Computer Vision,
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C. Allene,
J.-Y. Audibert,
J. Couprie, M.and Cousty,
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Some links between min-cuts, optimal spanning forests and watersheds.
In Proc. 8th International Symposium on Mathematical Morphology,
Rio de Janeiro, Brazil,
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J.-Y. Audibert.
Progressive mixture rules are deviation suboptimal.
In Advances in Neural Information Processing Systems,
volume 20,
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J.-Y. Audibert,
R. Munos,
and C. Szepesvari.
Tuning bandit algorithms in stochastic environments.
In 18th International Conference on Algorithmic Learning Theory,
Japon,
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F. Bach and Z. Harchaoui.
DIFFRAC: a discriminative and flexible framework for clustering.
In Advances in Neural Information Processing Systems,
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I. Eckstein,
J.-P. Pons,
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Generalized surface flows for mesh processing.
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P. Etyngier,
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In 1st International Conference on Scale Space and Variational Methods in Computer Vision,
Ishia, Italy,
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P. Etyngier,
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Projection Onto a Shape Manifold for Image Segmentation with Prior.
In 14th IEEE International Conference on Image Processing,
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P. Etyngier,
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Active-Contour-Based Image Segmentation using Machine Learning Techniques.
In 10th IEEE International Conference on Medical Image Computing and Computer Assisted Intervention,
Brisbane, Australia,
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P. Etyngier,
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Shape priors using Manifold Learning Techniques.
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Toward Manifold-Adaptive Learning.
In NIPS Workshop on Topology learning,
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Accurate, Dense, and Robust Multi-View Stereopsis..
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Testing for Homogeneity with Kernel Fisher Discriminant Analysis.
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P. Sahbi, H., Etyngier,
J.-Y. Audibert,
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CERTIS,
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2006
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Y. Furukawa,
A. Sethi,
J. Ponce,
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Robust Structure and Motion from Outlines of Smooth Curved Surfaces.
IEEE Transactions on Pattern Analysis and Machine Intelligence,
28(2):302-315,
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S. Lazebnik,
C. Schmid,
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A Discriminative Framework for Texture and Object Recognition Using Local Image Features.
Toward Category-Level Object Recognition, Springer-Verlag Lecture Notes in Computer Science,
2006.
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J. Ponce,
T. Berg,
M. Everingham,
D. Forsyth,
M. Hebert,
S. Lazebnik,
M. Marszalek,
C. Schmid,
B. Russell,
A. Torralba,
C. Williams,
J. Zhang,
and A. Zisserman.
Dataset Issues in Object Recognition.
Toward Category-Level Object Recognition, Springer-Verlag Lecture Notes in Computer Science,
2006.
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F. Rothganger,
S. Lazebnik,
C. Schmid,
and J. Ponce.
3D Object Modeling and Recognition Using Local Affine-Invariant Image Descriptors and Multi-View Spatial Constraints.
International Journal of Computer Vision,
66(3):231-259,
2006.
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F. Rothganger,
S. Lazebnik,
C. Schmid,
and J. Ponce.
3D Object Modeling and Recognition from Photographs and Image Sequences.
Toward Category-Level Object Recognition, Springer-Verlag Lecture Notes in Computer Science,
2006.
Conference articles
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Y. Furukawa and J. Ponce.
Carved Visual Hulls for Image-Based Modeling.
In European Conference on Computer Vision,
volume I,
pages 564-577,
2006.
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A. Kushal and J. Ponce.
Modeling 3D Objects from Stereo Views and Recognizing them in Photographs.
In European Conference on Computer Vision,
volume II,
pages 563-574,
2006.
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A. Kushal,
M. Rahurkar,
L. Fei-Fei,
J. Ponce,
and T. Huang.
Audio-Visual Speaker Localization Using Graphical Models.
In International Conference on Pattern Recognition,
2006.
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S. Lazebnik,
C. Schmid,
and J. Ponce.
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories.
In IEEE Conference on Computer Vision and Pattern Recognition,
volume II,
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2006.
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K. McHenry and J. Ponce.
A Geodesic Active Contour Framework for Finding Glass.
In IEEE Conference on Computer Vision and Pattern Recognition,
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2003
Books and proceedings
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D.A. Forsyth and J. Ponce.
Computer Vision: A Modern Approach.
Prentice-Hall,
2003.