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PlueckerNet: Learn to Register 3D Line Reconstructions
LiuLiu, HongdongLi, HaodongYao....
Published date-12/02/2020
Aligning two partially-overlapped 3D line reconstructions in Euclidean space is challenging, as we need to simultaneously solve correspondences and relative pose between line reconstructions. This paper proposes a neural network …
Top-1 CORSMAL Challenge 2020 Submission: Filling Mass Estimation Using Multi-modal Observations of Human-robot Handovers
VladimirIashin, FrancescaPalermo, GökhanSolak....
Published date-12/02/2020
Human-robot object handover is a key skill for the future of human-robot collaboration. CORSMAL 2020 Challenge focuses on the perception part of this problem: the robot needs to estimate the …
PatchmatchNet: Learned Multi-View Patchmatch Stereo
FangjinhuaWang, SilvanoGalliani, ChristophVogel....
Published date-12/02/2020
We present PatchmatchNet, a novel and learnable cascade formulation of Patchmatch for high-resolution multi-view stereo. With high computation speed and low memory requirement, PatchmatchNet can process higher resolution imagery and …
Partially Shared Semi-supervised Deep Matrix Factorization with Multi-view Data
HaonanHuang, NaiyaoLiang, WeiYan....
Published date-12/02/2020
MULTI-VIEWLEARNING
Since many real-world data can be described from multiple views, multi-view learning has attracted considerable attention. Various methods have been proposed and successfully applied to multi-view learning, typically based on …
Policy Supervectors: General Characterization of Agents by their Behaviour
AnssiKanervisto, TomiKinnunen, VilleHautamäki....
Published date-12/02/2020
DecisionMaking, ImitationLearning
By studying the underlying policies of decision-making agents, we can learn about their shortcomings and potentially improve them. Traditionally, this has been done either by examining the agent's implementation, its …
Algebraically-Informed Deep Networks (AIDN): A Deep Learning Approach to Represent Algebraic Structures
MustafaHajij, GhadaZamzmi, MatthewDawson....
Published date-12/02/2020
One of the central problems in the interface of deep learning and mathematics is that of building learning systems that can automatically uncover underlying mathematical laws from observed data. In …