962 citations · 1.6k across the 20 of their papers we have counts for
24 papers
Towards the Probabilistic Fusion of Learned Priors into Standard Pipelines for 3D Reconstruction
Tristan Laidlow, Jan Czarnowski, Andrea Nicastro +2
The best way to combine the results of deep learning with standard 3D reconstruction pipelines remains an open problem. While systems that pass the output of traditional multi-view…
TermiNeRF: Ray Termination Prediction for Efficient Neural Rendering
Martin Piala, Ronald Clark
Volume rendering using neural fields has shown great promise in capturing and synthesizing novel views of 3D scenes. However, this type of approach requires querying the volume net…
Waypoint Planning Networks
Alexandru-Iosif Toma, Hussein Ali Jaafar, Hao-Ya Hsueh +4
With the recent advances in machine learning, path planning algorithms are also evolving; however, the learned path planning algorithms often have difficulty competing with success…
End-to-End Egospheric Spatial Memory
Daniel Lenton, Stephen James, Ronald Clark +1
Spatial memory, or the ability to remember and recall specific locations and objects, is central to autonomous agents' ability to carry out tasks in real environments. However, mos…
Ivy: Templated Deep Learning for Inter-Framework Portability
Daniel Lenton, Fabio Pardo, Fabian Falck +2
We introduce Ivy, a templated Deep Learning (DL) framework which abstracts existing DL frameworks. Ivy unifies the core functions of these frameworks to exhibit consistent call sig…
Unsupervised Path Regression Networks
Michal Pándy, Daniel Lenton, Ronald Clark
We demonstrate that challenging shortest path problems can be solved via direct spline regression from a neural network, trained in an unsupervised manner (i.e. without requiring g…