EDBT 2026 Demo / reviewers in the wild / expert
Danil Galeev
dblp:250/9595
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 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 |
Image and video processing · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Image and video processing › image segmentation
edge-based segmentation |
0.7 | 1 | 2023 | Contour-based Interactive Segmentation · IJCAI 2023 |
Image and video processing › image segmentation
interactive segmentation |
0.7 | 1 | 2023 | Contour-based Interactive Segmentation · IJCAI 2023 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Contour-based Interactive SegmentationabstractRecent advances in interactive segmentation (IS) allow speeding up and simplifying image editing and labeling greatly. The majority of modern IS approaches accept user input in the form of clicks. However, using clicks may require too many user interactions, especially when selecting small ob- jects, minor parts of an object, or a group of ob- jects of the same type. In this paper, we consider such a natural form of user interaction as a loose contour, and introduce a contour-based IS method. We evaluate the proposed method on the standard segmentation benchmarks, our novel UserContours dataset, and its subset UserContours-G containing difficult segmentation cases. Through experiments, we demonstrate that a single contour provides the same accuracy as multiple clicks, thus reducing the required amount of user interactions. Polina Popenova, Danil Galeev, Anna Vorontsova, Anton Konushin |
IJCAI | 2 |