3.2 Training-free

P178

ID	Year	Name	Note	Tags	Link
117	2023	TokenFlow: Consistent Diffusion Features for Consistent Video Editing
	2023	FateZero: Fusing Attentions for Zero-shot Text-based Video Editing	Attention map fusing for better temporal consistency - During DDIM inversion, save inverted self-/cross-attention maps - During editing, use some algorithms to blend inverted maps and generated maps

P187

More Works

	MeDM (Chu et al.) OpScal flow-based guidance for temporal consistency “MeDM: Mediagng Image Diffusion Models for Video-to Video Translagon with Temporal Correspondence Guidance,” arXiv 2023.
	Ground-A-Video (Jeong et al.) Improve temporal consistency via modified attention and optical flow “Ground-A-Video: Zero-shot Grounded Video Editing using Text-to-image Diffusion Models,” arXiv 2023.
	Gen-L-Video (Lorem et al.) Edit very long videos using existing generators “Gen-L-Video: Multi-Text to Long Video Generation via Temporal Co-Denoising,” arXiv 2023.
	FLATTEN (Cong et al.) Optical flow-guided attention for temporal consistency “Flatten: optical flow-guided attention for consistent text-to-video editing,” arXiv 2023.
	InFusion (Khandelwal et al.) Improve temporal consistency via fusing latents “InFusion: Inject and Attention Fusion for Multi Concept Zero-Shot Text-based Video Editing,” ICCVW 2023.
	Vid2Vid-Zero (Wang et al.) Improve temporal consistency via cross￾attention guidance and null-text inversion “Zero-Shot Video Editing Using Off-The-Shelf Image Diffusion Models,” arXiv 2023.

P194

✅ 对于输入文本的每个 wordtoken, 都可以通过 attentior map 找到图像中的大概位置，把要去除的 token mask 掉，剩下部分保留。生成图像则把非 token 部分 mask 掉，以此进行两部分的融合。

P197

✅ 基于不同信号的各种版的 control net.

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