10 citations · 10 across the 2 of their papers we have counts for
7 papers
MonteFloor: Extending MCTS for Reconstructing Accurate Large-Scale Floor Plans
Sinisa Stekovic, Mahdi Rad, Friedrich Fraundorfer +1
We propose a novel method for reconstructing floor plans from noisy 3D point clouds. Our main contribution is a principled approach that relies on the Monte Carlo Tree Search (MCTS…
ALCN: Adaptive Local Contrast Normalization
Mahdi Rad, Peter M. Roth, Vincent Lepetit
To make Robotics and Augmented Reality applications robust to illumination changes, the current trend is to train a Deep Network with training images captured under many different…
Measuring Generalisation to Unseen Viewpoints, Articulations, Shapes and Objects for 3D Hand Pose Estimation under Hand-Object Interaction
Anil Armagan, Guillermo Garcia-Hernando, Seungryul Baek +32
We study how well different types of approaches generalise in the task of 3D hand pose estimation under single hand scenarios and hand-object interaction. We show that the accuracy…
HOnnotate: A method for 3D Annotation of Hand and Object Poses
Shreyas Hampali, Mahdi Rad, Markus Oberweger +1
We propose a method for annotating images of a hand manipulating an object with the 3D poses of both the hand and the object, together with a dataset created using this method. Our…
Domain Transfer for 3D Pose Estimation from Color Images without Manual Annotations
Mahdi Rad, Markus Oberweger, Vincent Lepetit
We introduce a novel learning method for 3D pose estimation from color images. While acquiring annotations for color images is a difficult task, our approach circumvents this probl…
Making Deep Heatmaps Robust to Partial Occlusions for 3D Object Pose Estimation
Markus Oberweger, Mahdi Rad, Vincent Lepetit
We introduce a novel method for robust and accurate 3D object pose estimation from a single color image under large occlusions. Following recent approaches, we first predict the 2D…