Structured Indoor Modeling Supplementary Material

Re - Identification in the Function Space of Feature Warps Supplementary Material

This supplementary material accompanies the paper “ReIdentification in the Function Space of Feature Warps”. This supplementary material is structured as follows. • Section II gives an introduction to Dynamic Time Warping (DTW). We describe how the algorithm can be applied to get the warp functions we formulated through Eqn. (1)-(3) in Section IV of the main paper. We also provide the algorithm...

Facilitating and Exploring Planar Homogeneous Texture for Indoor Scene Understanding (Supplementary Material)

Supplementary Material for Human-centric Indoor Scene Synthesis Using Stochastic Grammar

Depth estimation Single-image depth estimation is a fundamental problem in computer vision, which has found broad applications in scene understanding, 3D modeling, and robotics. The problem is challenging since no reliable depth cues are available. In this task, the algorithms output a depth image based on a single RGB input image. To demonstrate the efficacy of our synthetic data, we compare t...

Joint Layout Estimation and Global Multi-View Registration for Indoor Reconstruction: Supplementary Material

In this supplementary material, we specify all the parameters mentioned in the paper and show all of the experimental results for qualitative evaluation, using four synthetic datasets of the augmented ICL-NUIM datasets [1] (Livingroom1, Livingroom2, Office1, and Office2), and six real-world datasets of the SUN3D datasets [4] (mit dorm next sj, mit lab hj, mit 76 458, harvard c9, harvard c3, and...

Supplementary material: Stronger findings from mass spectral data through multi-peak modeling

This document is the Supplementary Material document for the publication titled Stronger findings from mass spectral data through multi-peak modeling [6]. An R implementation and data are available at http://research.ics.aalto.fi/mi/software/peakANOVA/.