Google’s MaskGIT Outperforms SOTA Transformer Models on Conditional Image Generation and Accelerates Autoregressive Decoding by up to 64x | Synced
A Google Research team proposes Masked Generative Image Transformer (MaskGIT), a novel image synthesis paradigm that uses a bidirectional transformer decoder. MaskGIT significantly outperforms stat...
Source: Synced | AI Technology & Industry Review
A Google Research team proposes Masked Generative Image Transformer (MaskGIT), a novel image synthesis paradigm that uses a bidirectional transformer decoder. MaskGIT significantly outperforms state-of-the-art transformer models on the ImageNet dataset and accelerates autoregressive decoding by up to 64x.