18 citations · 19 across the 4 of their papers we have counts for
4 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…
DeepFusion: Real-Time Dense 3D Reconstruction for Monocular SLAM using Single-View Depth and Gradient Predictions
Tristan Laidlow, Jan Czarnowski, Stefan Leutenegger
While the keypoint-based maps created by sparse monocular simultaneous localisation and mapping (SLAM) systems are useful for camera tracking, dense 3D reconstructions may be desir…
Dense RGB-D-Inertial SLAM with Map Deformations
Tristan Laidlow, Michael Bloesch, Wenbin Li +1
While dense visual SLAM methods are capable of estimating dense reconstructions of the environment, they suffer from a lack of robustness in their tracking step, especially when th…
ILabel: Interactive Neural Scene Labelling
Shuaifeng Zhi, Edgar Sucar, Andre Mouton +3
Joint representation of geometry, colour and semantics using a 3D neural field enables accurate dense labelling from ultra-sparse interactions as a user reconstructs a scene in rea…