119 citations · 151 across the 4 of their papers we have counts for
6 papers
Joint Unsupervised Learning of Optical Flow and Egomotion with Bi-Level Optimization
Shihao Jiang, Dylan Campbell, Miaomiao Liu +2
We address the problem of joint optical flow and camera motion estimation in rigid scenes by incorporating geometric constraints into an unsupervised deep learning framework. Unlik…
Representation Learning on Unit Ball with 3D Roto-Translational Equivariance
Sameera Ramasinghe, Salman Khan, Nick Barnes +1
Convolution is an integral operation that defines how the shape of one function is modified by another function. This powerful concept forms the basis of hierarchical feature learn…
Higher-order Pooling of CNN Features via Kernel Linearization for Action Recognition
Anoop Cherian, Piotr Koniusz, Stephen Gould
Most successful deep learning algorithms for action recognition extend models designed for image-based tasks such as object recognition to video. Such extensions are typically trai…
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…
SPICE: Semantic Propositional Image Caption Evaluation
Peter Anderson, Basura Fernando, Mark Johnson +1
There is considerable interest in the task of automatically generating image captions. However, evaluation is challenging. Existing automatic evaluation metrics are primarily sensi…
On Differentiating Parameterized Argmin and Argmax Problems with Application to Bi-level Optimization
Stephen Gould, Basura Fernando, Anoop Cherian +3
Some recent works in machine learning and computer vision involve the solution of a bi-level optimization problem. Here the solution of a parameterized lower-level problem binds va…