most citedSeedance 1.0: Exploring the Boundaries of Video Generation Models

1 citations · 1 across the 7 of their papers we have counts for

collaborators

9 papers

cs.CV2025

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…

cs.CV2025★ 1 cited

Seedance 1.0: Exploring the Boundaries of Video Generation Models

Yu Gao, Haoyuan Guo, Tuyen Hoang +41

Notable breakthroughs in diffusion modeling have propelled rapid improvements in video generation, yet current foundational model still face critical challenges in simultaneously b…

cs.CV2025

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…

cs.CV2025

Autoregressive Adversarial Post-Training for Real-Time Interactive Video Generation

Shanchuan Lin, Ceyuan Yang, Hao He +6

Existing large-scale video generation models are computationally intensive, preventing adoption in real-time and interactive applications. In this work, we propose autoregressive a…

cs.CV2025

SeedVR2: One-Step Video Restoration via Diffusion Adversarial Post-Training

Jianyi Wang, Shanchuan Lin, Zhijie Lin +10

Recent advances in diffusion-based video restoration (VR) demonstrate significant improvement in visual quality, yet yield a prohibitive computational cost during inference. While…

cs.CV2025

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…

cs.CV2025

Diffusion Adversarial Post-Training for One-Step Video Generation

Shanchuan Lin, Xin Xia, Yuxi Ren +3

The diffusion models are widely used for image and video generation, but their iterative generation process is slow and expansive. While existing distillation approaches have demon…

cs.CV2025

SeedVR: Seeding Infinity in Diffusion Transformer Towards Generic Video Restoration

Jianyi Wang, Zhijie Lin, Meng Wei +5

Video restoration poses non-trivial challenges in maintaining fidelity while recovering temporally consistent details from unknown degradations in the wild. Despite recent advances…

cs.CV2024

Is Your Text-to-Image Model Robust to Caption Noise?

Weichen Yu, Ziyan Yang, Shanchuan Lin +5

In text-to-image (T2I) generation, a prevalent training technique involves utilizing Vision Language Models (VLMs) for image re-captioning. Even though VLMs are known to exhibit ha…