6 citations · 7 across the 5 of their papers we have counts for
5 papers
Contextualising Implicit Representations for Semantic Tasks
Theo W. Costain, Kejie Li, Victor A. Prisacariu
Prior works have demonstrated that implicit representations trained only for reconstruction tasks typically generate encodings that are not useful for semantic tasks. In this work,…
Approximating Continuous Convolutions for Deep Network Compression
Theo W. Costain, Victor Adrian Prisacariu
We present ApproxConv, a novel method for compressing the layers of a convolutional neural network. Reframing conventional discrete convolution as continuous convolution of paramet…
Towards Generalising Neural Implicit Representations
Theo W. Costain, Victor Adrian Prisacariu
Neural implicit representations have shown substantial improvements in efficiently storing 3D data, when compared to conventional formats. However, the focus of existing work has m…
Finding Non-Uniform Quantization Schemes using Multi-Task Gaussian Processes
Marcelo Gennari do Nascimento, Theo W. Costain, Victor Adrian Prisacariu
We propose a novel method for neural network quantization that casts the neural architecture search problem as one of hyperparameter search to find non-uniform bit distributions th…
Correspondence Networks with Adaptive Neighbourhood Consensus
Shuda Li, Kai Han, Theo W. Costain +2
In this paper, we tackle the task of establishing dense visual correspondences between images containing objects of the same category. This is a challenging task due to large intra…