55 citations · 143 across the 14 of their papers we have counts for
6 papers · 1 filter
Zero-Shot Learning from scratch (ZFS): leveraging local compositional representations
Tristan Sylvain, Linda Petrini, R Devon Hjelm
Zero-shot classification is a generalization task where no instance from the target classes is seen during training. To allow for test-time transfer, each class is annotated with s…
Cross-Modal Information Maximization for Medical Imaging: CMIM
Tristan Sylvain, Francis Dutil, Tess Berthier +4
In hospitals, data are siloed to specific information systems that make the same information available under different modalities such as the different medical imaging exams the pa…
Image-to-image Mapping with Many Domains by Sparse Attribute Transfer
Matthew Amodio, Rim Assouel, Victor Schmidt +3
Unsupervised image-to-image translation consists of learning a pair of mappings between two domains without known pairwise correspondences between points. The current convention is…
Object-Centric Image Generation from Layouts
Tristan Sylvain, Pengchuan Zhang, Yoshua Bengio +2
Despite recent impressive results on single-object and single-domain image generation, the generation of complex scenes with multiple objects remains challenging. In this paper, we…
Locality and compositionality in zero-shot learning
Tristan Sylvain, Linda Petrini, Devon Hjelm
In this work we study locality and compositionality in the context of learning representations for Zero Shot Learning (ZSL). In order to well-isolate the importance of these proper…
Joint Learning of Generative Translator and Classifier for Visually Similar Classes
ByungIn Yoo, Tristan Sylvain, Yoshua Bengio +1
In this paper, we propose a Generative Translation Classification Network (GTCN) for improving visual classification accuracy in settings where classes are visually similar and dat…