TransGAN: Two Transformers Can Make One Strong GAN

14 Feb 2021 Yifan Jiang Shiyu Chang Zhangyang Wang

The recent explosive interest on transformers has suggested their potential to become powerful "universal" models for computer vision tasks, such as classification, detection, and segmentation. However, how further transformers can go - are they ready to take some more notoriously difficult vision tasks, e.g., generative adversarial networks (GANs)?.. (read more)

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Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Image Generation CelebA 64x64 TransGAN-XL FID 12.23 # 3
Image Generation CIFAR-10 TransGAN-XL Inception score 8.63 # 16
FID 11.89 # 18
Image Generation STL-10 TransGAN FID 25.32 # 1
Inception score 10.10 # 1

Methods used in the Paper


METHOD TYPE
🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet