5 papers
Infinite-Homography as Robust Conditioning for Camera-Controlled Video Generation
Min-Jung Kim, Jeongho Kim, Hoiyeong Jin +2
Recent progress in video diffusion models has spurred growing interest in camera-controlled novel-view video generation for dynamic scenes, aiming to provide creators with cinemati…
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…
Reward-Weighted Sampling: Enhancing Non-Autoregressive Characteristics in Masked Diffusion LLMs
Daehoon Gwak, Minseo Jung, Junwoo Park +4
Masked diffusion models (MDMs) offer a promising non-autoregressive alternative for large language modeling. Standard decoding methods for MDMs, such as confidence-based sampling,…
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…
Spatiotemporal Skip Guidance for Enhanced Video Diffusion Sampling
Junha Hyung, Kinam Kim, Susung Hong +2
Diffusion models have emerged as a powerful tool for generating high-quality images, videos, and 3D content. While sampling guidance techniques like CFG improve quality, they reduc…