5 papers
SARA: Semantically Adaptive Relational Alignment for Video Diffusion Models
Jiesong Lian, Zixiang Zhou, Ruizhe Zhong +6
Recent video diffusion models (VDMs) synthesize visually convincing clips, yet still drop entities, mis-bind attributes, and weaken the interactions specified in the prompt. Repres…
GeRM: A Generative Rendering Model From Physically Realistic to Photorealistic
Jiayuan Lu, Rengan Xie, Xuancheng Jin +5
While physically-based rendering (PBR) simulates light transport that guarantees physical realism, achieving true photorealistic rendering (PRR) demands prohibitive time and labor,…
SkyReels-A2: Compose Anything in Video Diffusion Transformers
Zhengcong Fei, Debang Li, Di Qiu +8
This paper presents SkyReels-A2, a controllable video generation framework capable of assembling arbitrary visual elements (e.g., characters, objects, backgrounds) into synthesized…
SkyReels-A1: Expressive Portrait Animation in Video Diffusion Transformers
Di Qiu, Zhengcong Fei, Rui Wang +5
We present SkyReels-A1, a simple yet effective framework built upon video diffusion Transformer to facilitate portrait image animation. Existing methodologies still encounter issue…
MovieCharacter: A Tuning-Free Framework for Controllable Character Video Synthesis
Di Qiu, Zheng Chen, Rui Wang +4
Recent advancements in character video synthesis still depend on extensive fine-tuning or complex 3D modeling processes, which can restrict accessibility and hinder real-time appli…