GLOBER: Coherent Non-autoregressive Video Generation via Global Guided Video Decoder

Neural Information Processing Systems 

The goal of this work is to advance research on video generation methods. All experiments are conducted without conditional inputs. Figure 1: Genetated long videos with 128 frames on the Sky Time-lapse and UCF-101 datasets (4 frames skipped). A.5 Settings of Hyper Parameters The detailed settings of model hyper parameters are presented in Table 4. Table 4: Hyper-parameters of the video auto-encoder and the quantitative results on video reconstruction. Experimental settings on the UCF-101 dataset are the same for both conditional and unconditional video generation except given video descriptions.

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