TSRUs

2000년 도입 · 논문 1편에서 사용

TSRUs, or Transformation-based Spatial Recurrent Unit p, is a modification of a ConvGRU used in the TriVD-GAN architecture for video generation. It largely follows TSRUc, but computes each intermediate output in a fully sequential manner: like in TSRUc, $c$ is given access to $\hat{h}\_{t-1}$, but additionally, $u$ is given access to both outputs $\hat{h}\_{t-1}$ and $c$, so as to make an informed decision prior to mixing. This yields the following replacement for $u$: $$ u = \sigma\left(W\_{u} \star\_{n}\left[\hat{h}\_{t-1};c\right] + b\_{u} \right) $$ In these equations $\sigma$ and $\rho$ are the elementwise sigmoid and ReLU functions respectively and the $\star\_{n}$ represents a convolution with a kernel of size $n \times n$. Brackets are used to represent a feature concatenation.

출처: Transformation-based Adversarial Video Prediction on Large-Scale Data

소개 논문: Transformation-based Adversarial Video Prediction on Large-Scale Data