An Occupancy-Depth Generative Model of Multi-view Images
By Pau Gargallo, Peter F. Sturm, Sergi Pujades. 2007
25 citations recorded by the source corpus.
Subfields: Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Graphics and Computer-Aided Design
- Andreas Geiger
- Jitendra Malik
- Ali O. Ulusoy
- Marc Pollefeys
- Michael J. Black
- Christian Häne
- Shubham Tulsiani
- Lubor Ladicky
In Computer Vision and Pattern Recognition
- Jitendra Malik
- Luc Van Gool
- Andreas Geiger
- Ming-Hsuan Yang
- Andrea Vedaldi
- Dacheng Tao
- Xiaogang Wang
- Trevor Darrell
Citations in the corpus
- Multi-view Supervision for Single-View Reconstruction via Differentiable Ray Consistency (2017, background): “It is also possible, by jointly modeling appearance and occupancy, to recover 3D structure of objects/scenes from multiple images via ray-potential based optimization [7, 23] or inference in a generative model [12].”
- Patches, Planes and Probabilities: A Non-Local Prior for Volumetric 3D Reconstruction (2016, background): “Previous works impose smoothness constraints via pairwise potentials that encourage adjacent voxels to take on the same occupancy state [18, 31] or condition surface orientations on semantic information [40].”
- Semantic Multi-view Stereo: Jointly Estimating Objects and Voxels (2017, methodology): “More recent approaches [13,22,30,33,34] phrase volumetric reconstruction as inference in an MRF where voxels along each pixel’s line of sight are connected via high-order ray potentials.”
- Semantic 3D Reconstruction with Continuous Regularization and Ray Potentials Using a Visibility Consistency Constraint (2016, methodology): “This was formulated in [25, 9, 21, 22, 31] as a problem of finding a voxel labeling in terms of color and occupancy such that the first occupied voxel along a ray has a similar color as the pixel it projects to.”
- Towards Probabilistic Volumetric Reconstruction Using Ray Potentials (2015, methodology): “In contrast, [10, 20] decouple voxel appearance estimation from the inference of occupancies and [28] does not model voxel appearance but instead relies on pre-estimated depth maps.”