most citedSeedance 1.0: Exploring the Boundaries of Video Generation Models

1 citations · 1 across the 3 of their papers we have counts for

collaborators

7 papers

cs.CV20251 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

Mogao: An Omni Foundation Model for Interleaved Multi-Modal Generation

Chao Liao, Liyang Liu, Xun Wang +7

Recent progress in unified models for image understanding and generation has been impressive, yet most approaches remain limited to single-modal generation conditioned on multiple…

cs.CV2025

DanceGRPO: Unleashing GRPO on Visual Generation

Zeyue Xue, Jie Wu, Yu Gao +8

Recent advances in generative AI have revolutionized visual content creation, yet aligning model outputs with human preferences remains a critical challenge. While Reinforcement Le…

cs.CV2025

Seedream 3.0 Technical Report

Yu Gao, Lixue Gong, Qiushan Guo +28

We present Seedream 3.0, a high-performance Chinese-English bilingual image generation foundation model. We develop several technical improvements to address existing challenges in…

cs.CV2025

Seedream 2.0: A Native Chinese-English Bilingual Image Generation Foundation Model

Lixue Gong, Xiaoxia Hou, Fanshi Li +25

Rapid advancement of diffusion models has catalyzed remarkable progress in the field of image generation. However, prevalent models such as Flux, SD3.5 and Midjourney, still grappl…

cs.CV2024

Prompt-A-Video: Prompt Your Video Diffusion Model via Preference-Aligned LLM

Yatai Ji, Jiacheng Zhang, Jie Wu +9

Text-to-video models have made remarkable advancements through optimization on high-quality text-video pairs, where the textual prompts play a pivotal role in determining quality o…