activity
20162019
most citedMatterport3D: Learning from RGB-D Data in Indoor Environments

337 citations · 389 across the 4 of their papers we have counts for

collaborators

9 papers

cs.CV2019

End-to-End CAD Model Retrieval and 9DoF Alignment in 3D Scans

Armen Avetisyan, Angela Dai, Matthias Nießner

We present a novel, end-to-end approach to align CAD models to an 3D scan of a scene, enabling transformation of a noisy, incomplete 3D scan to a compact, CAD reconstruction with c…

cs.CV201951 cited

Deferred Neural Rendering: Image Synthesis using Neural Textures

Justus Thies, Michael Zollhöfer, Matthias Nießner

The modern computer graphics pipeline can synthesize images at remarkable visual quality; however, it requires well-defined, high-quality 3D content as input. In this work, we expl…

cs.CV20171 cited

IMU2Face: Real-time Gesture-driven Facial Reenactment

Justus Thies, Michael Zollhöfer, Matthias Nießner

We present IMU2Face, a gesture-driven facial reenactment system. To this end, we combine recent advances in facial motion capture and inertial measurement units (IMUs) to control t…

cs.CV2017

Multiframe Scene Flow with Piecewise Rigid Motion

Vladislav Golyanik, Kihwan Kim, Robert Maier +3

We introduce a novel multiframe scene flow approach that jointly optimizes the consistency of the patch appearances and their local rigid motions from RGB-D image sequences. In con…

cs.CV2017337 cited

Matterport3D: Learning from RGB-D Data in Indoor Environments

Angel Chang, Angela Dai, Thomas Funkhouser +6

Access to large, diverse RGB-D datasets is critical for training RGB-D scene understanding algorithms. However, existing datasets still cover only a limited number of views or a re…

cs.GR2017

Calipso: Physics-based Image and Video Editing through CAD Model Proxies

Nazim Haouchine, Frederick Roy, Hadrien Courtecuisse +2

We present Calipso, an interactive method for editing images and videos in a physically-coherent manner. Our main idea is to realize physics-based manipulations by running a full p…