Text-to-Video Editing
4 papers with code • 0 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in Text-to-Video Editing
Most implemented papers
FateZero: Fusing Attentions for Zero-shot Text-based Video Editing
chenyangqiqi/fatezero
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ICCV 2023
We also have a better zero-shot shape-aware editing ability based on the text-to-video model.
ControlVideo: Conditional Control for One-shot Text-driven Video Editing and Beyond
This paper presents \emph{ControlVideo} for text-driven video editing -- generating a video that aligns with a given text while preserving the structure of the source video.
Gen-L-Video: Multi-Text to Long Video Generation via Temporal Co-Denoising
To address this challenge, we introduce a novel paradigm dubbed as Gen-L-Video, capable of extending off-the-shelf short video diffusion models for generating and editing videos comprising hundreds of frames with diverse semantic segments without introducing additional training, all while preserving content consistency.
Contextualized Diffusion Models for Text-Guided Image and Video Generation
To address this issue, we propose a novel and general contextualized diffusion model (ContextDiff) by incorporating the cross-modal context encompassing interactions and alignments between text condition and visual sample into forward and reverse processes.
