Search Results for author:
Found 9 papers, 2 papers with code
Thinking Outside the Box: Generation of Unconstrained 3D Room Layouts
We propose a method for room layout estimation that does not rely on the typical box approximation or Manhattan world assumption.
GroSS Decomposition: Group-Size Series Decomposition for Whole Search-Space Training
We present Group-size Series (GroSS) decomposition, a mathematical formulation of tensor factorisation into a series of approximations of increasing rank terms.
GroSS: Group-Size Series Decomposition for Grouped Architecture Search
We present a novel approach which is able to explore the configuration of grouped convolutions within neural networks.
FlowNet3D++: Geometric Losses For Deep Scene Flow Estimation
We present FlowNet3D++, a deep scene flow estimation network.
Correspondence Networks with Adaptive Neighbourhood Consensus
This is a challenging task due to large intra-class variations and a lack of dense pixel level annotations.
Ranked #11 on
Semantic correspondence
on PF-PASCAL
LaLaLoc: Latent Layout Localisation in Dynamic, Unvisited Environments
We present LaLaLoc to localise in environments without the need for prior visitation, and in a manner that is robust to large changes in scene appearance, such as a full rearrangement of furniture.
Cos R-CNN for Online Few-shot Object Detection
We propose Cos R-CNN, a simple exemplar-based R-CNN formulation that is designed for online few-shot object detection.
Project Aria: A New Tool for Egocentric Multi-Modal AI Research
Egocentric, multi-modal data as available on future augmented reality (AR) devices provides unique challenges and opportunities for machine perception.
SceneScript: Reconstructing Scenes With An Autoregressive Structured Language Model
We introduce SceneScript, a method that directly produces full scene models as a sequence of structured language commands using an autoregressive, token-based approach.
