Roxels: responsibility weighted 3D volume reconstruction
By Jeremy S. De Bonet, Paul A. Viola. 1999
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Jitendra Malik
- Shubham Tulsiani
- Tomas Simon
- Angjoo Kanazawa
- Tinghui Zhou
- Andrea Vedaldi
- Jiajun Wu
- Abhinav Kumar Gupta
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].”
- Towards Robust Voxel-Coloring: Handling Camera Calibration Errors and Partial Emptiness of Surface Voxels (2006, background): “Some work on handling this error in voxel-coloring can be found in the literature [6, 15, 10, 8, 14, 9].”
- Neural volumes (2019, methodology): “Volumetric reconstruction methods side-step this problem of explicit correspondence matching, beginning with Voxel Coloring [Prock and Dyer 1998; Seitz and Dyer 1997, 1999] and Space Carving [Bonet and Viola 1999; Broadhurst et al. 2001; Kutulakos and Seitz 2000].”
- 3D Reconstruction by Shadow Carving: Theory and Practical Evaluation (2007, unknown): “An alternative approach is photo-consistency, as introduced by the work of Seitz and Dyer [33], Kutulakos and Seitz [14] and numerous extensions and/or alternative formulations [34, 35, 36, 37, 38, 39, 40].”
- Methods for Volumetric Reconstruction of Visual Scenes (2004, background): “Therefore, we make no attempt to model blended colors that arise from transparency [10] or depth discontinuities [50].”