7 citations · 15 across the 5 of their papers we have counts for
6 papers
Virtual Adversarial Ladder Networks For Semi-supervised Learning
Saki Shinoda, Daniel E. Worrall, Gabriel J. Brostow
Semi-supervised learning (SSL) partially circumvents the high cost of labeling data by augmenting a small labeled dataset with a large and relatively cheap unlabeled dataset drawn…
Interpretable Transformations with Encoder-Decoder Networks
Daniel E. Worrall, Stephan J. Garbin, Daniyar Turmukhambetov +1
Deep feature spaces have the capacity to encode complex transformations of their input data. However, understanding the relative feature-space relationship between two transformed…
Responsive Action-based Video Synthesis
Corneliu Ilisescu, Halil Aytac Kanaci, Matteo Romagnoli +2
We propose technology to enable a new medium of expression, where video elements can be looped, merged, and triggered, interactively. Like audio, video is easy to sample from the r…
Hierarchical Subquery Evaluation for Active Learning on a Graph
Oisin Mac Aodha, Neill D. F. Campbell, Jan Kautz +1
To train good supervised and semi-supervised object classifiers, it is critical that we not waste the time of the human experts who are providing the training labels. Existing acti…
Becoming the Expert - Interactive Multi-Class Machine Teaching
Edward Johns, Oisin Mac Aodha, Gabriel J. Brostow
Compared to machines, humans are extremely good at classifying images into categories, especially when they possess prior knowledge of the categories at hand. If this prior informa…
Context Tricks for Cheap Semantic Segmentation
Thanapong Intharah, Gabriel J. Brostow
Accurate semantic labeling of image pixels is difficult because intra-class variability is often greater than inter-class variability. In turn, fast semantic segmentation is hard b…