/video_reconstruction_using_vp_detection_results

Primary LanguagePython

Video reconstruction using vp detection results

Used sources

How to use

  • set enviroment
cd cvpr22
conda create -y -n vpd
conda activate vpd
conda env update --file config/environment.yml

  • download models data
    download

  • make dirs

    • cvpr22
      • saved_results
        • nyu
        • scannet
        • su3
    • neurVPS
      • saved_results
        • scannet
        • su3
        • tmm17

  • modify cvpr code in video_predict.py and predict.py

    • img_size: video_predict.py 35 line
    • weight_name: predict.py 123 line

  • run python code

cd cvpr22 # or cd neurVPS
python video_predict.py nyu #scannet su3

Specification

name info
os ubuntu18.04
cpu Intel(R) Core(TM) i7-6700K CPU @ 4.00GHz
gpu GeForce RTX 2080 Ti Rev. A
ram 16G

Libraries

name version
python 3.7.0
pytorch 1.12.0-cuda11.3-cudnn8
numpy 1.21.2
matplotlib 3.2.2
opencv-python 4.8.0.74
scipy 1.7.3
scikit-image 0.18.3

Metrics

  • Performance
    name sec per frame(avg)
    NYU(cvpr) 0.20 sec
    ScanNet(cvpr) 0.17 sec
    SU3(cvpr) 0.18 sec
    SU3(neur) 1.09 sec
    ScanNet(neur) 1.20 sec
    TMM17(neur) 0.85 sec
  • AA(Angular Accuracy) Graph
    • cvpr
      img1
    • neur
      img2
    • all
      img3

SnapShot

  • cvpr NYU Dataset Result
    img4

Reference paper

(cvpr) https://arxiv.org/abs/2203.08586
(neurVPS) https://arxiv.org/abs/1910.06316