259 citations · 309 across the 10 of their papers we have counts for
10 papers
Deep Action- and Context-Aware Sequence Learning for Activity Recognition and Anticipation
Mohammad Sadegh Aliakbarian, Fatemehsadat Saleh, Basura Fernando +3
Action recognition and anticipation are key to the success of many computer vision applications. Existing methods can roughly be grouped into those that extract global, context-awa…
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…
Built-in Foreground/Background Prior for Weakly-Supervised Semantic Segmentation
Fatemehsadat Saleh, Mohammad Sadegh Ali Akbarian, Mathieu Salzmann +3
Pixel-level annotations are expensive and time consuming to obtain. Hence, weak supervision using only image tags could have a significant impact in semantic segmentation. Recently…
Optimizing Over Radial Kernels on Compact Manifolds
Sadeep Jayasumana, Richard Hartley, Mathieu Salzmann +2
We tackle the problem of optimizing over all possible positive definite radial kernels on Riemannian manifolds for classification. Kernel methods on Riemannian manifolds have recen…
A Framework for Shape Analysis via Hilbert Space Embedding
Sadeep Jayasumana, Mathieu Salzmann, Hongdong Li +1
We propose a framework for 2D shape analysis using positive definite kernels defined on Kendall's shape manifold. Different representations of 2D shapes are known to generate diffe…
Kernel Methods on the Riemannian Manifold of Symmetric Positive Definite Matrices
Sadeep Jayasumana, Richard Hartley, Mathieu Salzmann +2
Symmetric Positive Definite (SPD) matrices have become popular to encode image information. Accounting for the geometry of the Riemannian manifold of SPD matrices has proven key to…