oooolga/Ctrl-V
👆Pytorch implementation of "Ctrl-V: Higher Fidelity Video Generation with Bounding-Box Controlled Object Motion"
This project helps researchers and developers in autonomous driving simulate realistic video footage of vehicles and pedestrians. You input existing video datasets, and it outputs new videos where object movements, like cars changing lanes or pedestrians crossing, are precisely controlled by bounding boxes. This is ideal for those working on training and testing self-driving car algorithms.
No commits in the last 6 months.
Use this if you need to generate high-fidelity video scenarios with specific, controlled object motion for autonomous vehicle research and development.
Not ideal if you are looking for a general-purpose video generation tool not focused on autonomous driving datasets or fine-grained object control.
Stars
33
Forks
2
Language
Python
License
Apache-2.0
Category
Last pushed
Jul 28, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/oooolga/Ctrl-V"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
AliaksandrSiarohin/first-order-model
This repository contains the source code for the paper First Order Motion Model for Image Animation
kenziyuliu/MS-G3D
[CVPR 2020 Oral] PyTorch implementation of "Disentangling and Unifying Graph Convolutions for...
yoyo-nb/Thin-Plate-Spline-Motion-Model
[CVPR 2022] Thin-Plate Spline Motion Model for Image Animation.
sergeytulyakov/mocogan
MoCoGAN: Decomposing Motion and Content for Video Generation
DK-Jang/motion_puzzle
Motion Puzzle - Official PyTorch implementation