human evaluation
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Identity Decoupling for Multi-Subject Personalization of Text-to-Image Models
In this work, we present MuDI, a novel framework that enables multi-subject personalization by effectively decoupling identities from multiple subjects.
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Rethinking Human Evaluation Protocol for Text-to-Video Models: Enhancing Reliability, Reproducibility, and Practicality
Despite these strides, evaluating these models poses substantial challenges.
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Approximating Interactive Human Evaluation with Self-Play for Open-Domain Dialog Systems
Building an open-domain conversational agent is a challenging problem.
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High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks
Ruben Villegas, Arkanath Pathak, Harini Kannan, Dumitru Erhan, Quoc V. Le, Honglak Lee
Neural Information Processing Systems http://nips.cc/
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Subject-driven Text-to-Image Generation via Apprenticeship Learning Wenhu Chen Hexiang Hu Y andong Li Nataniel Ruiz Xuhui Jia Ming-Wei Chang William W. Cohen Google Deepmind
Subject-driven image generation is related to text-driven image editing but often needs to perform more sophisticated transformations to source images (e.g., rotating the view, zooming in/out, changing the pose of
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