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README

LOMM (ICCV 2025)

Latest Object Memory Management for Temporally Consistent Video Instance Segmentation Paper | Project

News

  • We release our code with trained models 2025.09.17
  • Our paper has also been accepted to MemVis: The 1st Workshop on Memory and Vision at ICCV 2025 2025.08.30

Data preparation & Installation

See Datasets & Installation

Getting Started

See Getting Started with LOMM

Model Zoo

We provide our trained models here

Citation

@article{lee2025latest,
  title={Latest Object Memory Management for Temporally Consistent Video Instance Segmentation},
  author={Lee, Seunghun and Seo, Jiwan and Choi, Minwoo and Han, Kiljoon and Jeong, Jaehoon and Durante, Zane and Adeli, Ehsan and Park, Sang Hyun and Im, Sunghoon},
  journal={arXiv preprint arXiv:2507.19754},
  year={2025}
}

Core symbols most depended-on inside this repo

cat
called by 90
lomm/data_video/utils.py
get
called by 88
demo_video/predictor.py
to
called by 41
mask2former/utils/misc.py
to
called by 38
lomm/data_video/utils.py
clone
called by 30
lomm/data_video/utils.py
info
called by 28
mask2former_video/data_video/datasets/ytvis_api/ytvos.py
info
called by 20
lomm/data_video/datasets/ytvis_api/ytvos.py
retry_if_cuda_oom
called by 11
mask2former_video/utils/memory.py

Shape

Method 646
Function 193
Class 163

Languages

Python100%
C++1%

Modules by API surface

mask2former/modeling/backbones_vitAdapter/adapter.py43 symbols
mask2former/modeling/backbones_samAdapter/adapter.py43 symbols
lomm/lomm.py40 symbols
mask2former_video/modeling/transformer_decoder/video_mask2former_transformer_decoder.py32 symbols
mask2former/modeling/transformer_decoder/mask2former_transformer_decoder.py32 symbols
mask2former/modeling/backbone/swin.py32 symbols
lomm/data_video/augmentation.py28 symbols
mask2former/modeling/backbones_samAdapter/backbones.py25 symbols
mask2former/modeling/transformer_decoder/transformer.py24 symbols
demo_video/predictor.py24 symbols
lomm/lomm_tracker.py23 symbols
mask2former/modeling/backbones_vitAdapter/backbones.py22 symbols

For agents

$ claude mcp add LOMM \
  -- python -m otcore.mcp_server <graph>

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