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DensePose: Dense Human Pose Estimation in the Wild
In this work we establish dense correspondences between an RGB image and a surface-based representation of the human body, a task we refer to as dense human pose estimation. We gather denseExpand
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Houdini: Fooling Deep Structured Prediction Models
Generating adversarial examples is a critical step for evaluating and improving the robustness of learning machines. So far, most existing methods only work for classification and are not designed toExpand
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Multi-scale Deep Learning for Gesture Detection and Localization
We present a method for gesture detection and localization based on multi-scale and multi-modal deep learning. Each visual modality captures spatial information at a particular spatial scale (such asExpand
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Dense Pose Transfer
In this work we integrate ideas from surface-based modeling with neural synthesis: we propose a combination of surface-based pose estimation and deep generative models that allows us to performExpand
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Object Level Visual Reasoning in Videos
Human activity recognition is typically addressed by detecting key concepts like global and local motion, features related to object classes present in the scene, as well as features related to theExpand
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A Multi-scale Approach to Gesture Detection and Recognition
We propose a generalized approach to human gesture recognition based on multiple data modalities such as depth video, articulated pose and speech. In our system, each gesture is decomposed intoExpand
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Lighting Estimation in Indoor Environments from Low-Quality Images
Lighting conditions estimation is a crucial point in many applications. In this paper, we show that combining color images with corresponding depth maps (provided by modern depth sensors) allows toExpand
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Slim DensePose: Thrifty Learning From Sparse Annotations and Motion Cues
DensePose supersedes traditional landmark detectors by densely mapping image pixels to body surface coordinates. This power, however, comes at a greatly increased annotation cost, as supervising theExpand
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Hand pose estimation through semi-supervised and weakly-supervised learning
We propose a method for hand pose estimation based on a deep regressor trained on two different kinds of input. Raw depth data is fused with an intermediate representation in the form of aExpand
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Houdini: Fooling Deep Structured Visual and Speech Recognition Models with Adversarial Examples
Generating adversarial examples is a critical step for evaluating and improving the robustness of learning machines. So far, most existing methods only work for classification and are not designed toExpand
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