no code implementations • 8 Oct 2018 • Hadi Salman, Payman Yadollahpour, Tom Fletcher, Kayhan Batmanghelich
We use a neural network to parametrize the smooth vector field and a recursive neural network (RNN) for approximating the solution of the ODE.
no code implementations • 5 Sep 2017 • Payman Yadollahpour
The task is often cast as a structured output problem on an exponentially large output-space, which is typically modeled by a discrete probabilistic model.
1 code implementation • CVPR 2015 • Mohammadreza Mostajabi, Payman Yadollahpour, Gregory Shakhnarovich
We introduce a purely feed-forward architecture for semantic segmentation.
1 code implementation • NeurIPS 2013 • Behnam Neyshabur, Payman Yadollahpour, Yury Makarychev, Ruslan Salakhutdinov, Nathan Srebro
When approximating binary similarity using the hamming distance between short binary hashes, we show that even if the similarity is symmetric, we can have shorter and more accurate hashes by using two distinct code maps.
no code implementations • CVPR 2013 • Payman Yadollahpour, Dhruv Batra, Gregory Shakhnarovich
This paper introduces a two-stage approach to semantic image segmentation.