Tiny Video Networks

Code

• github.com/google-research/google-research/tree/master/tiny_video_nets
  Officialtf★ 0
• github.com/DELTA37/TVN
  pytorch★ 0

Abstract

Video understanding is a challenging problem with great impact on the abilities of autonomous agents working in the real-world. Yet, solutions so far have been computationally intensive, with the fastest algorithms running for more than half a second per video snippet on powerful GPUs. We propose a novel idea on video architecture learning - Tiny Video Networks - which automatically designs highly efficient models for video understanding. The tiny video models run with competitive performance for as low as 37 milliseconds per video on a CPU and 10 milliseconds on a standard GPU.

Tasks

Reproductions