5 papers
Structure from Articulated Motion: Accurate and Stable Monocular 3D Reconstruction without Training Data
Onorina Kovalenko, Vladislav Golyanik, Jameel Malik +2
Recovery of articulated 3D structure from 2D observations is a challenging computer vision problem with many applications. Current learning-based approaches achieve state-of-the-ar…
HDM-Net: Monocular Non-Rigid 3D Reconstruction with Learned Deformation Model
Vladislav Golyanik, Soshi Shimada, Kiran Varanasi +1
Monocular dense 3D reconstruction of deformable objects is a hard ill-posed problem in computer vision. Current techniques either require dense correspondences and rely on motion a…
Accurate 3D Reconstruction of Dynamic Scenes from Monocular Image Sequences with Severe Occlusions
Vladislav Golyanik, Torben Fetzer, Didier Stricker
The paper introduces an accurate solution to dense orthographic Non-Rigid Structure from Motion (NRSfM) in scenarios with severe occlusions or, likewise, inaccurate correspondences…
Scalable Dense Monocular Surface Reconstruction
Mohammad Dawud Ansari, Vladislav Golyanik, Didier Stricker
This paper reports on a novel template-free monocular non-rigid surface reconstruction approach. Existing techniques using motion and deformation cues rely on multiple prior assump…
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…