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I am a research scientist at Naver Labs Europe working on computer vision and machine learning. I did my PhD at INSA Lyon advised by Christian Wolf and Julien Mille. I have also spent time at Google, Simon Fraser University and University of Guelph during my PhD journey. I received my Engineer's degree (MSc) from ENSAI. |
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We propose a model learned in a unsupervised manner which is able to perform counterfactual predictions in pixel space. |
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We show that Mocap data can be used for improving image-based and video-based human mesh recovery methods. We propose a video-based transformer model called PoseBERT which is trained on synthetic data only. |
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We introduce a new problem of counterfactual learning of object mechanics from visual input and a benchmark called CoPhy. |
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Self-supervised video representation by leveraging ASR and long videos via noise contrastive estimation. |
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A model capable of learning to reason about semantically meaningful spatio-temporal interactions in videos. |
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Human activity recogntion using skeleton data and RGB. We propose a network able to focus on relevant parts of the RGB stream given deep features extracted from the pose stream. |
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We propose a new method for human action recognition relying on RGB data only. A visual attention module is able to extract glimpses within each frame. Resulting local descriptors are soft-assigned to distributed workers which are finally classifying the video. |
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A new spatio-temporal attention based mechanism for human action recognition able to automatically attend to most important human hands and detect the most discriminative moments in an action. |
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We introduce a new dataset for Domain Adaptation and show a comparaison between shallow and deep methods based on Maximum Mean Discrepancy. |
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We introduce an attention-based mechanism around hands on RGB videos conditioned on features extracted from human 3D pose. |
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We introduce a new method based on Conditional Maximum Mean Discrepancy for domain adaptation on image classification. |
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