33 citations · 62 across the 6 of their papers we have counts for
7 papers
EMPNet: Neural Localisation and Mapping Using Embedded Memory Points
Gil Avraham, Yan Zuo, Thanuja Dharmasiri +1
Continuously estimating an agent's state space and a representation of its surroundings has proven vital towards full autonomy. A shared common ground among systems which successfu…
Look No Deeper: Recognizing Places from Opposing Viewpoints under Varying Scene Appearance using Single-View Depth Estimation
Sourav Garg, Madhu Babu, Thanuja Dharmasiri +5
Visual place recognition (VPR) - the act of recognizing a familiar visual place - becomes difficult when there is extreme environmental appearance change or viewpoint change. Parti…
Real-Time Joint Semantic Segmentation and Depth Estimation Using Asymmetric Annotations
Vladimir Nekrasov, Thanuja Dharmasiri, Andrew Spek +3
Deployment of deep learning models in robotics as sensory information extractors can be a daunting task to handle, even using generic GPU cards. Here, we address three of its most…
CReaM: Condensed Real-time Models for Depth Prediction using Convolutional Neural Networks
Andrew Spek, Thanuja Dharmasiri, Tom Drummond
Since the resurgence of CNNs the robotic vision community has developed a range of algorithms that perform classification, semantic segmentation and structure prediction (depths, n…
ENG: End-to-end Neural Geometry for Robust Depth and Pose Estimation using CNNs
Thanuja Dharmasiri, Andrew Spek, Tom Drummond
Recovering structure and motion parameters given a image pair or a sequence of images is a well studied problem in computer vision. This is often achieved by employing Structure fr…
Just-in-Time Reconstruction: Inpainting Sparse Maps using Single View Depth Predictors as Priors
Chamara Saroj Weerasekera, Thanuja Dharmasiri, Ravi Garg +2
We present ``just-in-time reconstruction" as real-time image-guided inpainting of a map with arbitrary scale and sparsity to generate a fully dense depth map for the image. In part…
Joint Prediction of Depths, Normals and Surface Curvature from RGB Images using CNNs
Thanuja Dharmasiri, Andrew Spek, Tom Drummond
Understanding the 3D structure of a scene is of vital importance, when it comes to developing fully autonomous robots. To this end, we present a novel deep learning based framework…