myungsub

Papers from Super SloMo references

• Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation [Paper]
  • Huaizu Jiang, Deqing Sun, Varun Jampani, Ming-Hsuan Yang, Erik Learned-Miller, Jan Kautz
  • CVPR 2018 (splotlight)
• Video frame synthesis using deep voxel flow [Paper] [Code]
  • Z. Liu, R. Yeh, X. Tang, Y. Liu, and A. Agarwala.
  • ICCV 2017
• Video frame interpolation via adaptive separable convolution. [Paper] [Code]

tejaslodaya

import multiprocessing
import pandas as pd
import numpy as np

def _apply_df(args):
    df, func, num, kwargs = args
    return num, df.apply(func, **kwargs)

def apply_by_multiprocessing(df,func,**kwargs):
  workers=kwargs.pop('workers')

0xjac

The repository for the assignment is public and Github does not allow the creation of private forks for public repositories.

The correct way of creating a private frok by duplicating the repo is documented here.

For this assignment the commands are:

1. Create a bare clone of the repository. (This is temporary and will be removed so just do it wherever.)

git clone --bare [email protected]:usi-systems/easytrace.git

EncodeTS

VGG-Face model for Keras

This is the Keras model of VGG-Face.

It has been obtained through the following method:

• vgg-face-keras:directly convert the vgg-face matconvnet model to keras model
• vgg-face-keras-fc:first convert vgg-face caffe model to mxnet model,and then convert it to keras model

Details about the network architecture can be found in the following paper:

samklr

#! /bin/bash
wget https://github.com/google/protobuf/releases/download/v2.6.1/protobuf-2.6.1.tar.gz
tar xzf protobuf-2.6.1.tar.gz
cd protobuf-2.6.1
sudo apt-get update
sudo apt-get install build-essential
sudo ./configure
sudo make
sudo make check
sudo make install 

kevin-smets

Default

Powerlevel10k