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Found 3 papers, 1 papers with code
DOCTR: Disentangled Object-Centric Transformer for Point Scene Understanding
In this work, we propose a novel Disentangled Object-Centric TRansformer (DOCTR) that explores object-centric representation to facilitate learning with multiple objects for the multiple sub-tasks in a unified manner.
DOR3D-Net: Dense Ordinal Regression Network for 3D Hand Pose Estimation
Recently, dense regression methods have attracted increasing attention in 3D hand pose estimation task, which provide a low computational burden and high accuracy regression way by densely regressing hand joint offset maps.
DVI-SLAM: A Dual Visual Inertial SLAM Network
Recent deep learning based visual simultaneous localization and mapping (SLAM) methods have made significant progress.
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