4 citations · 14 across the 38 of their papers we have counts for
11 papers · 1 filter
Canvas-to-Image: Compositional Image Generation with Multimodal Controls
Yusuf Dalva, Guocheng Gordon Qian, Maya Goldenberg +5
While modern diffusion models excel at generating high-quality and diverse images, they still struggle with high-fidelity compositional and multimodal control, particularly when us…
Diverse Video Generation with Determinantal Point Process-Guided Policy Optimization
Tahira Kazimi, Connor Dunlop, Pinar Yanardag
While recent text-to-video (T2V) diffusion models have achieved impressive quality and prompt alignment, they often produce low-diversity outputs when sampling multiple videos from…
Personalized Image Editing in Text-to-Image Diffusion Models via Collaborative Direct Preference Optimization
Connor Dunlop, Matthew Zheng, Kavana Venkatesh +1
Text-to-image (T2I) diffusion models have made remarkable strides in generating and editing high-fidelity images from text. Yet, these models remain fundamentally generic, failing…
Infinity-RoPE: Action-Controllable Infinite Video Generation Emerges From Autoregressive Self-Rollout
Hidir Yesiltepe, Tuna Han Salih Meral, Adil Kaan Akan +2
Current autoregressive video diffusion models are constrained by three core bottlenecks: (i) the finite temporal horizon imposed by the base model's 3D Rotary Positional Embedding…
LoRAverse: A Submodular Framework to Retrieve Diverse Adapters for Diffusion Models
Mert Sonmezer, Matthew Zheng, Pinar Yanardag
Low-rank Adaptation (LoRA) models have revolutionized the personalization of pre-trained diffusion models by enabling fine-tuning through low-rank, factorized weight matrices speci…
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…
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…
Dynamic View Synthesis as an Inverse Problem
Hidir Yesiltepe, Pinar Yanardag
In this work, we address dynamic view synthesis from monocular videos as an inverse problem in a training-free setting. By redesigning the noise initialization phase of a pre-train…
LoRAShop: Training-Free Multi-Concept Image Generation and Editing with Rectified Flow Transformers
Yusuf Dalva, Hidir Yesiltepe, Pinar Yanardag
We introduce LoRAShop, the first framework for multi-concept image editing with LoRA models. LoRAShop builds on a key observation about the feature interaction patterns inside Flux…
CREA: A Collaborative Multi-Agent Framework for Creative Image Editing and Generation
Kavana Venkatesh, Connor Dunlop, Pinar Yanardag
Creativity in AI imagery remains a fundamental challenge, requiring not only the generation of visually compelling content but also the capacity to add novel, expressive, and artis…
ConceptAttention: Diffusion Transformers Learn Highly Interpretable Features
Alec Helbling, Tuna Han Salih Meral, Ben Hoover +2
Do the rich representations of multi-modal diffusion transformers (DiTs) exhibit unique properties that enhance their interpretability? We introduce ConceptAttention, a novel metho…