6 papers · 1 filter
TextGuider: Training-Free Guidance for Text Rendering via Attention Alignment
Kanghyun Baek, Sangyub Lee, Jin Young Choi +6
Despite recent advances, diffusion-based text-to-image models still struggle with accurate text rendering. Several studies have proposed fine-tuning or training-free refinement met…
DCText: Scheduled Attention Masking for Visual Text Generation via Divide-and-Conquer Strategy
Jaewoo Song, Jooyoung Choi, Kanghyun Baek +3
Despite recent text-to-image models achieving highfidelity text rendering, they still struggle with long or multiple texts due to diluted global attention. We propose DCText, a tra…
Negative-Guided Subject Fidelity Optimization for Zero-Shot Subject-Driven Generation
Chaehun Shin, Jooyoung Choi, Johan Barthelemy +2
We present Subject Fidelity Optimization (SFO), a novel comparative learning framework for zero-shot subject-driven generation that enhances subject fidelity. Existing supervised f…
EdiText: Controllable Coarse-to-Fine Text Editing with Diffusion Language Models
Che Hyun Lee, Heeseung Kim, Jiheum Yeom +1
We propose EdiText, a controllable text editing method that modifies the reference text to desired attributes at various scales. We integrate an SDEdit-based editing technique that…
Does Your Voice Assistant Remember? Analyzing Conversational Context Recall and Utilization in Voice Interaction Models
Heeseung Kim, Che Hyun Lee, Sangkwon Park +4
Recent advancements in multi-turn voice interaction models have improved user-model communication. However, while closed-source models effectively retain and recall past utterances…
CNN-based TEM image denoising from first principles
Jinwoong Chae, Sungwook Hong, Sungkyu Kim +2
Transmission electron microscope (TEM) images are often corrupted by noise, hindering their interpretation. To address this issue, we propose a deep learning-based approach using s…