Sliced Wasserstein Generative Models

In generative modeling, the Wasserstein distance (WD) has emerged as a useful metric to measure the discrepancy between generated and real data distributions. Unfortunately, it is challenging to approximate the WD of high-dimensional distributions... (read more)

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Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK BENCHMARK
Image Generation CelebA-HQ 1024x1024 PG-SWGAN FID 5.5 # 2
Image Generation LSUN Bedroom 256 x 256 PG-SWGAN FID 8.0 # 5
Video Generation TrailerFaces PG-SWGAN-3D FID 404.1 # 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