activity
20142024
most citedPlaying Doom with SLAM-Augmented Deep Reinforcement Learning

45 citations · 102 across the 23 of their papers we have counts for

collaborators

8 papers

cs.CV20222 cited

Memory-Driven Text-to-Image Generation

Bowen Li, Philip H. S. Torr, Thomas Lukasiewicz

We introduce a memory-driven semi-parametric approach to text-to-image generation, which is based on both parametric and non-parametric techniques. The non-parametric component is…

cs.CV20227 cited

SiamMask: A Framework for Fast Online Object Tracking and Segmentation

Weiming Hu, Qiang Wang, Li Zhang +2

In this paper we introduce SiamMask, a framework to perform both visual object tracking and video object segmentation, in real-time, with the same simple method. We improve the off…

cs.CV2016

ROAM: a Rich Object Appearance Model with Application to Rotoscoping

Ondrej Miksik, Juan-Manuel Pérez-Rúa, Philip H. S. Torr +1

Rotoscoping, the detailed delineation of scene elements through a video shot, is a painstaking task of tremendous importance in professional post-production pipelines. While pixel-…

cs.LG20161 cited

Learning to superoptimize programs - Workshop Version

Rudy Bunel, Alban Desmaison, M. Pawan Kumar +2

Superoptimization requires the estimation of the best program for a given computational task. In order to deal with large programs, superoptimization techniques perform a stochasti…

cs.AI201645 cited

Playing Doom with SLAM-Augmented Deep Reinforcement Learning

Shehroze Bhatti, Alban Desmaison, Ondrej Miksik +3

A number of recent approaches to policy learning in 2D game domains have been successful going directly from raw input images to actions. However when employed in complex 3D enviro…

cs.CV2016

Efficient Linear Programming for Dense CRFs

Thalaiyasingam Ajanthan, Alban Desmaison, Rudy Bunel +3

The fully connected conditional random field (CRF) with Gaussian pairwise potentials has proven popular and effective for multi-class semantic segmentation. While the energy of a d…