https://github.com/adymaharana/storydalle
공식 코드StoryDALL-E: Adapting Pretrained Text-to-Image Transformers for Story Continuation
Papers with Code 아카이브
Story Continuation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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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
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/appleternity/story-plot-generation
공식 코드Conveying the Predicted Future to Users: A Case Study of Story Plot Prediction
https://github.com/google/storybench
공식 코드StoryBench: A Multifaceted Benchmark for Continuous Story Visualization
https://github.com/minnesotanlp/diversity-extraction-from-llms
공식 코드How Far Can We Extract Diverse Perspectives from Large Language Models?
https://github.com/sixiaozheng/contextualstory
공식 코드ContextualStory: Consistent Visual Storytelling with Spatially-Enhanced and Storyline Context
https://github.com/xichenpan/ARLDM
공식 코드Synthesizing Coherent Story with Auto-Regressive Latent Diffusion Models
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.