[CVPR 2024] Intelligent Grimm - Open-ended Visual Storytelling via Latent Diffusion Models
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Updated
Apr 15, 2024 - Python
[CVPR 2024] Intelligent Grimm - Open-ended Visual Storytelling via Latent Diffusion Models
We designed an end-to-end framework that encourage interactive narrative experience based on keyword control and image generation.
In our "Introduction to Machine Learning" assignment, we have undertaken a comprehensive examination of the fundamental aspects of ML. This exploration spans the foundational principles of probability, advanced data wrangling techniques, the art of visual storytelling, methodologies in clustering and topic modeling, and the neural networks.
[Course] Inteligencia Artificial en la Universidad Nacional de Colombia - Sede La Paz
A list of research papers on knowledge-enhanced multimodal learning
Information Design / Data Visualization about meteors
PyTorch code for Automatic generation of comic dialogues. The purpose of this project is to generate subsequent dialogues given a multimodal context.
Part of ther @SketchTheDocs family of projects. A visual puzzle game to test your tech IQ. Featured segment on #HelloWorld (on Microsoft LearnTV) every Thursday @1:30pm EST.
Parse a narrative XML from draw.io through R to ink
Graph convolution-based visual storytelling
DATA-X: m130 - Introduction to Visual Principles Using Matplotlib and Seaborn. Provides users with the necessary foundations for building and understanding current state of the art visualizations. An additional aim is to provide users with an understanding of both the theory and techniques of various visualization paradigms. Finally, this series…
Code for the ACL paper "No Metrics Are Perfect: Adversarial Reward Learning for Visual Storytelling"
Visual Storytelling with Cross-Modal Rules
An implementation of the paper "Contextualize, Show and Tell: A Neural Visual Storyteller." presented at the Storytelling Workshop, co-located with NAACL 2018.
Implementation of seq2seq model for Visual Storytelling Challenge (VIST) http://visionandlanguage.net/VIST/index.html
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