SOTAVerified

Story Continuation

The task involves providing an initial scene that can be obtained in real world use cases. By including this scene, a model can then copy and adapt elements from it as it generates subsequent images.

Source: StoryDALL-E: Adapting Pretrained Text-to-Image Transformers for Story Continuation

Papers

No papers found.

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1StoryDALL-E (Story Embeddings + Cross-Attention)FID36.28Unverified
2StoryDALL-E (Cross-Attention)FID35.04Unverified
3StoryDALL-E (Story Embeddings)FID29.21Unverified
4StoryDALL-EFID28.37Unverified
5AR-LDMFID19.28Unverified
6ContextualStoryFID16.33Unverified
#ModelMetricClaimedVerifiedStatus
1StoryDALL-E (Story Embeddings + Cross-Attention)FID31.68Unverified
2StoryDALL-E (Story Embeddings)FID30.45Unverified
3StoryDALL-E (Cross-Attention)FID23.27Unverified
4StoryDALL-EFID21.64Unverified
5AR-LDMFID17.4Unverified
6ContextualStoryFID14.2Unverified
#ModelMetricClaimedVerifiedStatus
1AR-LDM (DII captions)FID17.03Unverified
2AR-LDM (SIS captions)FID16.95Unverified