EDBT 2026 Demo / reviewers in the wild / expert
David Barmherzig
dblp:211/7202 · also David A. Barmherzig
· DBLP profile ↗
2ranked-venue papers
1as first author
2since 2021 · last 2025
0000-0003-2466-981XORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 2 · 1 first-author · 2 since 2021Artificial intelligence and machine learning · 1 · 1 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.
| Computer graphics and multimedia
1 paper |
Computational photography and imaging · 100% | |
| Artificial intelligence
1 paper |
3D vision · 100% |
Topics — the 3 heaviest of 3, 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 | Opportunistic Single-Photon Time of Flight · CVPR 2025 |
Computational photography and imaging
single-photon imaging |
0.9 | 1 | 2025 | Opportunistic Single-Photon Time of Flight · CVPR 2025 |
Computational photography and imaging
time-of-flight imaging |
0.9 | 1 | 2025 | Opportunistic Single-Photon Time of Flight · CVPR 2025 |
Methods — techniques the papers use, named apart from their topics
frequency-domain analysis · 1.7SPAD camera · 1.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Opportunistic Single-Photon Time of FlightabstractScattered light from pulsed lasers is increasingly part of our ambient illumination, as many devices rely on them for active 3D sensing. In this work, we ask: can these “ambient” light signals be detected and leveraged for passive 3D vision? We show that pulsed lasers, despite being weak and fluctuating at MHz to GHz frequencies, leave a distinctive sinc comb pattern in the temporal frequency domain of incident flux that is specific to each laser and invariant to the scene. This enables their passive detection and analysis with a free-running SPAD camera, even when they are unknown, asynchronous, out of sight, and emitting concurrently. We show how to synchronize with such lasers computationally, characterize their pulse emissions, separate their contributions, and—if many are present—localize them in 3D and recover a depth map of the camera’s field of view. We use our camera prototype to demonstrate (1) a first-of-its-kind visualization of asynchronously propagating light pulses from multiple lasers through the same scene, (2) passive estimation of a laser’s MHz-scale pulse repetition frequency with mHz precision, and (3) mm-scale 3D imaging over room-scale distances by passively harvesting photons from two or more out-of-view lasers. Sotiris Nousias, Mian Wei, Howard Xiao, Maxx Wu, Shahmeer Athar, Kevin J. Wang, Anagh Malik, David Barmherzig, David B. Lindell, Kiriakos N. Kutulakos |
CVPR | 8 |
| 2021 | Recovering Missing Data in Coherent Diffraction ImagingabstractA method is presented for inferring missing low-frequency data in coherent diffraction imaging via the least-squares solution of a linear system. This gives rise to improved image reconstruction when solving the phase retrieval problem. David Barmherzig, Alex H. Barnett, Charles L. Epstein, Leslie Greengard, Jeremy F. Magland, Manas Rachh |
SIAM J. Imaging Sci. | 1 |