7 papers
SkipSR: Faster Super Resolution with Token Skipping
Rohan Choudhury, Shanchuan Lin, Jianyi Wang +6
Diffusion-based super-resolution (SR) is a key component in video generation and video restoration, but is slow and expensive, limiting scalability to higher resolutions and longer…
Growing Visual Generative Capacity for Pre-Trained MLLMs
Hanyu Wang, Jiaming Han, Ziyan Yang +6
Multimodal large language models (MLLMs) extend the success of language models to visual understanding, and recent efforts have sought to build unified MLLMs that support both unde…
Vision as a Dialect: Unifying Visual Understanding and Generation via Text-Aligned Representations
Jiaming Han, Hao Chen, Yang Zhao +6
This paper presents a multimodal framework that attempts to unify visual understanding and generation within a shared discrete semantic representation. At its core is the Text-Alig…
Seaweed-7B: Cost-Effective Training of Video Generation Foundation Model
Team Seawead, Ceyuan Yang, Zhijie Lin +52
This technical report presents a cost-efficient strategy for training a video generation foundation model. We present a mid-sized research model with approximately 7 billion parame…
Synthetic Video Enhances Physical Fidelity in Video Synthesis
Qi Zhao, Xingyu Ni, Ziyu Wang +4
We investigate how to enhance the physical fidelity of video generation models by leveraging synthetic videos derived from computer graphics pipelines. These rendered videos respec…
CameraCtrl II: Dynamic Scene Exploration via Camera-controlled Video Diffusion Models
Hao He, Ceyuan Yang, Shanchuan Lin +7
This paper introduces CameraCtrl II, a framework that enables large-scale dynamic scene exploration through a camera-controlled video diffusion model. Previous camera-conditioned v…