167 citations · 421 across the 14 of their papers we have counts for
16 papers
CNNs are Globally Optimal Given Multi-Layer Support
Chen Huang, Chen Kong, Simon Lucey
Stochastic Gradient Descent (SGD) is the central workhorse for training modern CNNs. Although giving impressive empirical performance it can be slow to converge. In this paper we e…
Take it in your stride: Do we need striding in CNNs?
Chen Kong, Simon Lucey
Since their inception, CNNs have utilized some type of striding operator to reduce the overlap of receptive fields and spatial dimensions. Although having clear heuristic motivatio…
Learning Depth from Monocular Videos using Direct Methods
Chaoyang Wang, Jose Miguel Buenaposada, Rui Zhu +1
The ability to predict depth from a single image - using recent advances in CNNs - is of increasing interest to the vision community. Unsupervised strategies to learning are partic…
Semantic Photometric Bundle Adjustment on Natural Sequences
Rui Zhu, Chaoyang Wang, Chen-Hsuan Lin +2
The problem of obtaining dense reconstruction of an object in a natural sequence of images has been long studied in computer vision. Classically this problem has been solved throug…
Object-Centric Photometric Bundle Adjustment with Deep Shape Prior
Rui Zhu, Chaoyang Wang, Chen-Hsuan Lin +2
Reconstructing 3D shapes from a sequence of images has long been a problem of interest in computer vision. Classical Structure from Motion (SfM) methods have attempted to solve thi…
Learning Policies for Adaptive Tracking with Deep Feature Cascades
Chen Huang, Simon Lucey, Deva Ramanan
Visual object tracking is a fundamental and time-critical vision task. Recent years have seen many shallow tracking methods based on real-time pixel-based correlation filters, as w…