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tal-mgcbm's Introduction

MGCSBM

Temporal Action Localization with Multi-granularity Feature Aggregation and Cross-level Boundary Modeling

Our code is built upon the codebase from ActionFormer,TemporalMaxer and Tridet, and we would like to express our gratitude for their outstanding work.

Environment

  • Ubuntu20.04
  • NVIDIA GeForce RTX 4090 GPU
  • Python3.8, Pytorch2.0 and CUDA11.8
  • h5py, joblib, matplotlib, numpy, pandas, PyYAML, scikit_learn, scipy, setuptools

Install NMS

cd ./libs/utils
python setup.py install --user
cd ../..

Data preparation

We use the same features as Tridet. To use these features, please download them from their link and unpack them into the ./data folder.

Pretrained Models

We provide our pre-trained models.

Google drive：https://drive.google.com/drive/folders/1x_q0s_QCNkVsXbZMN-2fc7AH2y3qk35E?usp=sharing

Training and Evaluation

Train: python ./train.py ./configs/xxxx.yaml --save_ckpt_dir ./ckpt/xxx

Eval: python ./eval.py ./configs/xxxx.yaml <path of the weights>

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