SVD_Xtend

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SVD_Xtend is an AI tool that provides Stable Video Diffusion training code and extensions. It enables finetuning of SVD models and tracklet-conditioned video generation for object movement control.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is SVD_Xtend?

SVD_Xtend offers comprehensive training code and extensions for Stable Video Diffusion, allowing users to finetune SVD models for customized video generation. A key feature is tracklet-conditioned video generation, which provides precise control over object movement within videos using bounding box information. The tool supports various video data processing methods, including the use of datasets like BDD100K, and offers detailed training configurations. It also integrates methods from Boximator and TrackDiffusion for enhanced control and instance-level manipulation. SVD_Xtend is ideal for AI researchers and developers looking to experiment with and advance video diffusion models.

Best used for

Ideal for AI researchers and developers who need to finetune Stable Video Diffusion models, generate videos with precise object movement control, and experiment with advanced video generation techniques. Especially valuable for those working on tracklet-conditioned video synthesis and model customization.

Common actions

train video models

generate controlled video

finetune diffusion models

"AI Agents"github copilotface swappingcollaborationautomated workflowdeepfakeworkflowslow-code/no-codeopen-source

Capabilities

Key features

SVD model finetuning
Tracklet-conditioned video generation
Video data processing
Customizable training configurations
Boximator/TrackDiffusion integration

Target Audience

professor

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What kind of video data can be used for training with SVD_Xtend?

SVD_Xtend is flexible and can use any video data for training, not just specific datasets like BDD100K. Users only need to modify the base folder in the DummyDataset logic and arrange their videos in a simple frame-by-frame file structure for the tool to process them effectively.

How does SVD_Xtend enable control over object movement in generated videos?

SVD_Xtend incorporates tracklet-conditioned video generation, building upon SVD. This allows users to control the movement of objects within the video using tracklets, which are bounding box information. This feature aims to provide more precise and controllable motion in the generated output.

What is the typical resolution used for video generation in SVD_Xtend?

The current implementation of SVD_Xtend uses a resolution of 512x320 for Stable Video Diffusion to generate videos. While this resolution might impact the perceived quality, the primary focus is on demonstrating the effectiveness of tracklet control, with plans to improve video quality in future updates.

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