8 citations · 11 across the 6 of their papers we have counts for
6 papers · 1 filter
BurstDeflicker: A Benchmark Dataset for Flicker Removal in Dynamic Scenes
Lishen Qu, Zhihao Liu, Shihao Zhou +5
Flicker artifacts in short-exposure images are caused by the interplay between the row-wise exposure mechanism of rolling shutter cameras and the temporal intensity variations of a…
Llama Learns to Direct: DirectorLLM for Human-Centric Video Generation
Kunpeng Song, Tingbo Hou, Zecheng He +12
In this paper, we introduce DirectorLLM, a novel video generation model that employs a large language model (LLM) to orchestrate human poses within videos. As foundational text-to-…
LinGen: Towards High-Resolution Minute-Length Text-to-Video Generation with Linear Computational Complexity
Hongjie Wang, Chih-Yao Ma, Yen-Cheng Liu +10
Text-to-video generation enhances content creation but is highly computationally intensive: The computational cost of Diffusion Transformers (DiTs) scales quadratically in the numb…
Movie Gen: A Cast of Media Foundation Models
Adam Polyak, Amit Zohar, Andrew Brown +85
We present Movie Gen, a cast of foundation models that generates high-quality, 1080p HD videos with different aspect ratios and synchronized audio. We also show additional capabili…
Animated Stickers: Bringing Stickers to Life with Video Diffusion
David Yan, Winnie Zhang, Luxin Zhang +15
We introduce animated stickers, a video diffusion model which generates an animation conditioned on a text prompt and static sticker image. Our model is built on top of the state-o…
AVID: Any-Length Video Inpainting with Diffusion Model
Zhixing Zhang, Bichen Wu, Xiaoyan Wang +6
Recent advances in diffusion models have successfully enabled text-guided image inpainting. While it seems straightforward to extend such editing capability into the video domain,…