167 citations · 520 across the 43 of their papers we have counts for
6 papers · 1 filter
Adversarial Framing for Image and Video Classification
Konrad Zolna, Michal Zajac, Negar Rostamzadeh +1
Neural networks are prone to adversarial attacks. In general, such attacks deteriorate the quality of the input by either slightly modifying most of its pixels, or by occluding it…
Domain-Adaptive Single-View 3D Reconstruction
Pedro O. Pinheiro, Negar Rostamzadeh, Sungjin Ahn
Single-view 3D shape reconstruction is an important but challenging problem, mainly for two reasons. First, as shape annotation is very expensive to acquire, current methods rely o…
Fashion-Gen: The Generative Fashion Dataset and Challenge
Negar Rostamzadeh, Seyedarian Hosseini, Thomas Boquet +4
We introduce a new dataset of 293,008 high definition (1360 x 1360 pixels) fashion images paired with item descriptions provided by professional stylists. Each item is photographed…
Where are the Blobs: Counting by Localization with Point Supervision
Issam H. Laradji, Negar Rostamzadeh, Pedro O. Pinheiro +2
Object counting is an important task in computer vision due to its growing demand in applications such as surveillance, traffic monitoring, and counting everyday objects. State-of-…
Uncertainty in Multitask Transfer Learning
Alexandre Lacoste, Boris Oreshkin, Wonchang Chung +3
Using variational Bayes neural networks, we develop an algorithm capable of accumulating knowledge into a prior from multiple different tasks. The result is a rich and meaningful p…
Hierarchical Adversarially Learned Inference
Mohamed Ishmael Belghazi, Sai Rajeswar, Olivier Mastropietro +3
We propose a novel hierarchical generative model with a simple Markovian structure and a corresponding inference model. Both the generative and inference model are trained using th…