978 citations · 7k across the 148 of their papers we have counts for
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Synthetic Humans for Action Recognition from Unseen Viewpoints
Gül Varol, Ivan Laptev, Cordelia Schmid +1
Although synthetic training data has been shown to be beneficial for tasks such as human pose estimation, its use for RGB human action recognition is relatively unexplored. Our goa…
Learning to Track Any Object
Achal Dave, Pavel Tokmakov, Cordelia Schmid +1
Object tracking can be formulated as "finding the right object in a video". We observe that recent approaches for class-agnostic tracking tend to focus on the "finding" part, but l…
Graph convolutional networks for learning with few clean and many noisy labels
Ahmet Iscen, Giorgos Tolias, Yannis Avrithis +2
In this work we consider the problem of learning a classifier from noisy labels when a few clean labeled examples are given. The structure of clean and noisy data is modeled by a g…
White-box vs Black-box: Bayes Optimal Strategies for Membership Inference
Alexandre Sablayrolles, Matthijs Douze, Yann Ollivier +2
Membership inference determines, given a sample and trained parameters of a machine learning model, whether the sample was part of the training set. In this paper, we derive the op…
Learning to combine primitive skills: A step towards versatile robotic manipulation
Robin Strudel, Alexander Pashevich, Igor Kalevatykh +3
Manipulation tasks such as preparing a meal or assembling furniture remain highly challenging for robotics and vision. Traditional task and motion planning (TAMP) methods can solve…
Moulding Humans: Non-parametric 3D Human Shape Estimation from Single Images
Valentin Gabeur, Jean-Sebastien Franco, Xavier Martin +2
In this paper, we tackle the problem of 3D human shape estimation from single RGB images. While the recent progress in convolutional neural networks has allowed impressive results…