Demo Data from EDBT 2026 / reviewers in the wild / expert
Uzay Gökay
dblp:414/8494
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2025
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 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.
| Artificial intelligence
1 paper |
Video understanding and tracking · 87% Representation and self-supervised learning · 13% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer vision › Video understanding and tracking
action segmentation |
0.9 | 1 | 2025 | Skeleton Motion Words for Unsupervised Skeleton-Based Temporal Action Segmentation · ICCV 2025 |
Computer vision › Video understanding and tracking › action segmentation › human action segmentation
skeleton-based action segmentation |
0.9 | 1 | 2025 | Skeleton Motion Words for Unsupervised Skeleton-Based Temporal Action Segmentation · ICCV 2025 |
Machine learning › Representation and self-supervised learning › representation learning
unsupervised representation learning |
0.3 | 1 | 2025 | Skeleton Motion Words for Unsupervised Skeleton-Based Temporal Action Segmentation · ICCV 2025 |
Methods — techniques the papers use, named apart from their topics
skeleton motion encoding · 0.9motion words · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Skeleton Motion Words for Unsupervised Skeleton-Based Temporal Action Segmentation
Uzay Gökay, Federico Spurio, Dominik R. Bach, Juergen Gall |
ICCV | 1 |