KlingTeam/360Motion-Dataset
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How to use KlingTeam/3DTrajMaster with Diffusers:
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("KlingTeam/3DTrajMaster", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]3DTrajMaster controls one or multiple entity motions in 3D space with entity-specific 3D trajectories for text-to-video (T2V) generation. It has the following features::
This is the implementation based on CogVideoX-5B. Please refer to our github for details on usage.
If you find this project useful, please consider citing:
@inproceedings{fu20243dtrajmaster,
author = {Fu, Xiao and Liu, Xian and Wang, Xintao and Peng, Sida and Xia, Menghan and Shi, Xiaoyu and Yuan, Ziyang and Wan, Pengfei and Zhang, Di and Lin, Dahua},
title = {3DTrajMaster: Mastering 3D Trajectory for Multi-Entity Motion in Video Generation},
booktitle = {ICLR},
year = {2025}
}