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Methods/TSRUs

TSRUs

SequentialIntroduced 20001 papers
Source Paper

Description

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, ccc is given access to h^_t−1\hat{h}\_{t-1}h^_t−1, but additionally, uuu is given access to both outputs h^_t−1\hat{h}\_{t-1}h^_t−1 and ccc, so as to make an informed decision prior to mixing. This yields the following replacement for uuu:

u=σ(W_u⋆_n[h^_t−1;c]+b_u)u = \sigma\left(W\_{u} \star\_{n}\left[\hat{h}\_{t-1};c\right] + b\_{u} \right)u=σ(W_u⋆_n[h^_t−1;c]+b_u)

In these equations σ\sigmaσ and ρ\rhoρ are the elementwise sigmoid and ReLU functions respectively and the ⋆_n\star\_{n}⋆_n represents a convolution with a kernel of size n×nn \times nn×n. Brackets are used to represent a feature concatenation.

Papers Using This Method

Transformation-based Adversarial Video Prediction on Large-Scale Data2020-03-09