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cs.CV2026

Physics in 2-Steps: Locking Motion Priors Before Visual Refinement Erases Them

Woojung Han, Seil Kang, Youngjun Jun +3

Image-to-Video diffusion models leverage input images to generate visually stunning content, yet frequently produce motion that violates physical laws. We reveal a surprising findi…

cs.CV2026

Real-Time Visual Attribution Streaming in Thinking Model

Seil Kang, Woojung Han, Junhyeok Kim +3

We present an amortized framework for real-time visual attribution streaming in multimodal thinking models. When these models generate code from a screenshot or solve math problems…

cs.CV2026

Interpretable Motion-Attentive Maps: Spatio-Temporally Localizing Concepts in Video Diffusion Transformers

Youngjun Jun, Seil Kang, Woojung Han +1

Video Diffusion Transformers (DiTs) have been synthesizing high-quality video with high fidelity from given text descriptions involving motion. However, understanding how Video DiT…

cs.CV2025

Pathology-Aware Adaptive Watermarking for Text-Driven Medical Image Synthesis

Chanyoung Kim, Dayun Ju, Jinyeong Kim +3

As recent text-conditioned diffusion models have enabled the generation of high-quality images, concerns over their potential misuse have also grown. This issue is critical in the…

cs.CV2025

Distilling Spectral Graph for Object-Context Aware Open-Vocabulary Semantic Segmentation

Chanyoung Kim, Dayun Ju, Woojung Han +2

Open-Vocabulary Semantic Segmentation (OVSS) has advanced with recent vision-language models (VLMs), enabling segmentation beyond predefined categories through various learning sch…

cs.CV2025

Spatial Transport Optimization by Repositioning Attention Map for Training-Free Text-to-Image Synthesis

Woojung Han, Yeonkyung Lee, Chanyoung Kim +2

Diffusion-based text-to-image (T2I) models have recently excelled in high-quality image generation, particularly in a training-free manner, enabling cost-effective adaptability and…