Demo Data from EDBT 2026 / reviewers in the wild / expert
SeonHwa Kim
dblp:415/0006
· DBLP profile ↗
1ranked-venue papers
0as 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 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.
| Artificial intelligence
1 paper |
Generative modeling · 100% | |
| Computer graphics and multimedia
1 paper |
Visual content generation and editing · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Generative modeling › conditional generative model
pose-guided generation |
0.9 | 1 | 2025 | Dual Recursive Feedback on Generation and Appearance Latents for Pose-Robust Text-to-Image Diffusion · ICCV 2025 |
Machine learning › Generative modeling › diffusion model › text-to-image generation
text-to-image diffusion model |
0.9 | 1 | 2025 | Dual Recursive Feedback on Generation and Appearance Latents for Pose-Robust Text-to-Image Diffusion · ICCV 2025 |
Visual content generation and editing
image generation |
0.3 | 1 | 2025 | Dual Recursive Feedback on Generation and Appearance Latents for Pose-Robust Text-to-Image Diffusion · ICCV 2025 |
Methods — techniques the papers use, named apart from their topics
feedback · 1.7diffusion model · 1.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Dual Recursive Feedback on Generation and Appearance Latents for Pose-Robust Text-to-Image Diffusion
Pu-Reum Kim, SeonHwa Kim, Soobin Park, Eun Ju Cha, Kyong Hwan Jin |
ICCV | 3 |