Pages

▼

EMPNet: Neural Localisation and Mapping Using Embedded Memory Points (with Gil Avraham, Yan Zuo and Thanuja Dharmasiri)

›
This paper shows how to compute dense descriptors over images that can be used to augment ICP for localisation from large baselines. [I...

Event-based motion segmentation by motion compensation (with Timo Stoffregen, Guillermo Gallego, Lindsay Kleeman and Davide Scaramuzza)

›
This paper shows how to solve simultaneous estimation of segmentation and motion estimation for events from a Neuromorphic (event) camera...

Adversarial Pulmonary Pathology Translation for Pairwise Chest X-Ray Data Augmentation (with Yunyan Xing, Zongyuan Ge, Rui Zeng, Dwarikanath Mahapatra, Jarrel Seah and Meng Law)

›
This paper shows how to use Generative Adversarial Networks (GANs) to augment data for classes that are rare in the dataset.  The expande...

Parallel optimal transport gan (with Gil Avraham and Yan Zuo)

›
This paper shows how to address the diversity problem in Generative Adversarial Networks by introducing a loss that explicitly pulls the ...

Look no deeper: Recognizing places from opposing viewpoints under varying scene appearance using single-view depth estimation (with Sourav Garg, Madhu Babu, Thanuja Dharmasiri, Stephen Hausler, Niko Suenderhauf, Swagat Kumar and Michael Milford)

›
This paper presents an approach to solving the hard problem of finding correspondences and localisation under extreme (180°) viewpoint va...

The Importance of Metric Learning for Robotic Vision: Open Set Recognition and Active Learning (with Ben Meyer)

›
This paper shows how to use metric learning for active learning.  In a metric space, examples of novel classes typically map to empty par...

Real-time joint semantic segmentation and depth estimation using asymmetric annotations (with Vladimir Nekrasov, Thanuja Dharmasiri, Andrew Spek, Chunhua Shen and Ian Reid)

›
This paper shows the benefits of simultaneously estimating semantics and depth for a monocular image input stream.  The resulting network...

Learning factorized representations for open-set domain adaptation (with Mahsa Baktashmotlagh, Masoud Faraki, and Mathieu Salzmann)

›
This paper describes how to learn representations that transfer well between domains, while acknowledging that the target domain may have c...

Eng: End-to-end neural geometry for robust depth and pose estimation using cnns (with Thanuja Dharmasiri and Andrew Spek)

›
This paper shows how to compute camera motion using networks to estimate depth per frame and optical flow between frames with uncertainty...

Traversing latent space using decision ferns (with Yan Zuo and Gil Avraham)

›
This paper shows how to use a controller (based on decision ferns) to impose structure on the latent space of an autoencoder. [ACCV 201...

Approximate Fisher Information Matrix to Characterize the Training of Deep Neural Networks (WITH Zhibin Liao, Ian Reid and Gustavo Carneiro)

›
This paper looks at how to measure the condition number of the training problem for deep networks, how this is affected by batch size and...

Deep metric learning and image classification with nearest neighbour gaussian kernels (with Ben Meyer and Ben Harwood)

›
This paper shows how embedding a Gaussian kernel density classifier in latent space can be used to learn metric space representations of ...

CReaM: Condensed real-time models for depth prediction using convolutional neural networks (with Andrew Spek and Thanuja Dharmasiri)

›
This paper shows how to use a complex model to train a simpler one by applying a loss to cause the embeddings in latent space to converge...

Relative pose based redundancy removal: Collaborative RGB-D data transmission in mobile visual sensor networks (with Xiaoqin Wang, Ahmet Şekercioğlu, Vincent Frémont, Enrico Natalizio and Isabelle Fantoni)

›
This paper shows how two robots that are exploring the same environment can share RGBD data to fill in gaps in each other's sensory d...

Efficient Subpixel Refinement with Symbolic Linear Predictors (with Vincent Lui, Jonathon Geeves and Winston Yii)

›
This paper introduces a method for very rapid sub-pixel refinement of correspondences.  The method precomputes an update matrix that appl...