activity
20242026
collaborators

5 papers

cs.CV2026

From Zero to Hero: Training-Free Custom Concept Spawning in World Models

Kiymet Akdemir, Pinar Yanardag

Autoregressive world models have emerged as a powerful paradigm for interactive video generation, allowing users to navigate dynamically generated environments through actions. The…

cs.CV2025

Plot'n Polish: Zero-shot Story Visualization and Disentangled Editing with Text-to-Image Diffusion Models

Kiymet Akdemir, Jing Shi, Kushal Kafle +2

Text-to-image diffusion models have demonstrated significant capabilities to generate diverse and detailed visuals in various domains, and story visualization is emerging as a part…

cs.CV2025

Audit & Repair: An Agentic Framework for Consistent Story Visualization in Text-to-Image Diffusion Models

Kiymet Akdemir, Tahira Kazimi, Pinar Yanardag

Story visualization has become a popular task where visual scenes are generated to depict a narrative across multiple panels. A central challenge in this setting is maintaining vis…

cs.CV2024

ORACLE: Leveraging Mutual Information for Consistent Character Generation with LoRAs in Diffusion Models

Kiymet Akdemir, Pinar Yanardag

Text-to-image diffusion models have recently taken center stage as pivotal tools in promoting visual creativity across an array of domains such as comic book artistry, children's l…

cs.CV2024

MIST: Mitigating Intersectional Bias with Disentangled Cross-Attention Editing in Text-to-Image Diffusion Models

Hidir Yesiltepe, Kiymet Akdemir, Pinar Yanardag

Diffusion-based text-to-image models have rapidly gained popularity for their ability to generate detailed and realistic images from textual descriptions. However, these models oft…