12 citations · 15 across the 2 of their papers we have counts for
4 papers · 1 filter
Unsupervised Learning of Landmarks by Descriptor Vector Exchange
James Thewlis, Samuel Albanie, Hakan Bilen +1
Equivariance to random image transformations is an effective method to learn landmarks of object categories, such as the eyes and the nose in faces, without manual supervision. How…
Slim DensePose: Thrifty Learning from Sparse Annotations and Motion Cues
Natalia Neverova, James Thewlis, Rıza Alp Güler +2
DensePose supersedes traditional landmark detectors by densely mapping image pixels to body surface coordinates. This power, however, comes at a greatly increased annotation time,…
Cross Pixel Optical Flow Similarity for Self-Supervised Learning
Aravindh Mahendran, James Thewlis, Andrea Vedaldi
We propose a novel method for learning convolutional neural image representations without manual supervision. We use motion cues in the form of optical flow, to supervise represent…
Unsupervised learning of object frames by dense equivariant image labelling
James Thewlis, Hakan Bilen, Andrea Vedaldi
One of the key challenges of visual perception is to extract abstract models of 3D objects and object categories from visual measurements, which are affected by complex nuisance fa…