Demo Data from SIGIR 2026 / reviewers in the wild / expert
Pierre-André Brousseau
dblp:259/5330
· DBLP profile ↗
3ranked-venue papers
3as first author
2since 2021 · last 2025
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 3 · 3 first-author · 2 since 2021Graphics, computer vision, multimedia, augmented reality and games · 3 · 3 first-author · 2 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Artificial intelligence
2 papers |
3D vision · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer vision › 3D vision
depth estimation |
0.9 | 1 | 2025 | Spherical Epipolar Rectification for Deep Two-View Absolute Depth Estimation · ICCV 2025 |
Computer vision › 3D vision › multi-view geometry
epipolar geometry |
0.9 | 1 | 2025 | Spherical Epipolar Rectification for Deep Two-View Absolute Depth Estimation · ICCV 2025 |
Computer vision › 3D vision
camera calibration |
0.4 | 1 | 2019 | Calibration of Axial Fisheye Cameras Through Generic Virtual Central Models · ICCV 2019 |
Computer vision › 3D vision › camera calibration
fisheye camera calibration |
0.4 | 1 | 2019 | Calibration of Axial Fisheye Cameras Through Generic Virtual Central Models · ICCV 2019 |
Methods — techniques the papers use, named apart from their topics
deep two-view estimation · 0.9structured light · 0.4generic virtual central model · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Spherical Epipolar Rectification for Deep Two-View Absolute Depth Estimation
Pierre-André Brousseau, Sébastien Roy 0001 |
ICCV | 1 |
| 2023 | Strong Stereo Features for Self-Supervised Practical Stereo Matching
Pierre-André Brousseau, Sébastien Roy 0001 |
BMVC | 1 |
| 2019 | Calibration of Axial Fisheye Cameras Through Generic Virtual Central ModelsabstractFisheye cameras are notoriously hard to calibrate using traditional plane-based methods. This paper proposes a new calibration method for large field of view cameras. Similarly to planar calibration, it relies on multiple images of a planar calibration grid with dense correspondences, typically obtained using structured light. By relying on the grids themselves instead of the distorted image plane, we can build a rectilinear Generic Virtual Central (GVC) camera. Instead of relying on a single GVC camera, our method proposes a selection of multiple GVC cameras which can cover any field of view and be trivially aligned to provide a very accurate generic central model. We demonstrate that this approach can directly model axial cameras, assuming the distortion center is located on the camera axis. Experimental validation is provided on both synthetic and real fisheye cameras featuring up to a 280° field of view. To our knowledge, this is one of the only practical methods to calibrate axial cameras. Pierre-André Brousseau, Sébastien Roy 0001 |
ICCV | 1 |