What Are You Doing? A Closer Look at Controllable Human Video Generation

摘要

High-quality benchmarks are crucial for driving progress in machine learning research. However, despite the growing interest in video generation, there is no comprehensive dataset to evaluate human synthesis. Humans can perform a wide variety of actions and interactions, but existing datasets, like TikTok, TED-Talks, and HumanVid, lack the diversity and complexity to fully capture the capabilities of video generation models. We close this gap by introducing 'What Are You Doing?' (WYD): a new benchmark for fine-grained evaluation of controllable image-to-video generation of humans. WYD consists of 1,544 captioned videos that have been meticulously collected and annotated with fine-grained categories. These allow us to systematically measure performance across 9 aspects of human generation, including actions, interactions and motion. We also propose an evaluation framework, where we adapt existing metrics for better human- and video-level assessment, as shown by human preference. Equipped with our dataset and metrics, we perform in-depth analyses of state-of-the-art open-source models in controllable image-to-video generation, showing how WYD provides novel insights about their capabilities. We release data and code to drive progress in human video generation.