5 papers · 1 filter
EgoX: Egocentric Video Generation from a Single Exocentric Video
Taewoong Kang, Kinam Kim, Dohyeon Kim +3
Egocentric perception enables humans to experience and understand the world directly from their own point of view. Translating exocentric (third-person) videos into egocentric (fir…
InsertAnywhere: Geometrically Grounded and Optics-Aware Video Object Insertion
Hoiyeong Jin, Hyojin Jang, Junha Hyung +6
Recent advances in diffusion models have enabled impressive video editing capabilities, yet production-grade Video Object Insertion (VOI) remains challenging due to inadequate 4D s…
ACG: Action Coherence Guidance for Flow-based Vision-Language-Action models
Minho Park, Kinam Kim, Junha Hyung +5
Diffusion and flow matching models have emerged as powerful robot policies, enabling Vision-Language-Action (VLA) models to generalize across diverse scenes and instructions. Yet,…
Cross-Frame Representation Alignment for Fine-Tuning Video Diffusion Models
Sungwon Hwang, Hyojin Jang, Kinam Kim +2
Fine-tuning Video Diffusion Models (VDMs) at the user level to generate videos that reflect specific attributes of training data presents notable challenges, yet remains underexplo…
Temporal In-Context Fine-Tuning with Temporal Reasoning for Versatile Control of Video Diffusion Models
Kinam Kim, Junha Hyung, Jaegul Choo
Recent advances in text-to-video diffusion models have enabled high-quality video synthesis, but controllable generation remains challenging, particularly under limited data and co…