Bojia Zi*,
Weixuan Peng*,
Xianbiao Qi†,
Jianan Wang, Shihao Zhao, Rong Xiao, Kam-Fai Wong
* Equal contribution. † Corresponding author.
MiniMax-Remover is a fast and effective video object remover based on minimax optimization. It operates in two stages: the first stage trains a remover using a simplified DiT architecture, while the second stage distills a robust remover with CFG removal and fewer inference steps.
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Fast: Requires only 6 inference steps and does not use CFG, making it highly efficient.
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Effective: Seamlessly removes objects from videos and generates high-quality visual content.
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Robust: Maintains robustness by preventing the regeneration of undesired objects or artifacts within the masked region, even under varying noise conditions.
All dependencies are listed in requirements.txt.
pip install -r requirements.txthuggingface-cli download zibojia/minimax-remover --include vae transformer scheduler --local-dir .import torch
from diffusers.utils import export_to_video
from decord import VideoReader
from diffusers.models import AutoencoderKLWan
from transformer_minimax_remover import Transformer3DModel
from diffusers.schedulers import UniPCMultistepScheduler
from pipeline_minimax_remover import Minimax_Remover_Pipeline
random_seed = 42
video_length = 81
device = torch.device("cuda:0")
# Load model weights separately
vae = AutoencoderKLWan.from_pretrained("./vae", torch_dtype=torch.float16)
transformer = Transformer3DModel.from_pretrained("./transformer", torch_dtype=torch.float16)
scheduler = UniPCMultistepScheduler.from_pretrained("./scheduler")
images = # images in range [-1, 1]
masks = # masks in range [0, 1]
# Initialize the pipeline (pass the loaded weights as objects)
pipe = Minimax_Remover_Pipeline(vae=vae, transformer=transformer, \
scheduler=scheduler, torch_dtype=torch.float16
).to(device)
result = pipe(images=images, masks=masks, num_frames=video_length, height=480, width=832, \
num_inference_steps=12, generator=torch.Generator(device=device).manual_seed(random_seed), iterations=6 \
).frames[0]
export_to_video(result, "./output.mp4")Feel free to send an email to 19210240030@fudan.edu.cn if you have any questions or suggestions.