X-Dance is a test dataset specifically for image-to-video animation generation, released in 2025 by Nanjing University in collaboration with Tencent and the Shanghai Artificial Intelligence Laboratory. The related research paper is titled "SteadyDancer: Harmonized and Coherent Human Image Animation with First-Frame PreservationThe study aims to evaluate the robustness and generalization ability of models in real-world scenarios when dealing with challenges such as identity preservation, temporal coherence, and spatiotemporal misalignment.

This dataset contains 12 driving videos, including 8 high-dynamic dance movements and 4 low-amplitude everyday behaviors, covering various non-ideal real-world scenarios such as motion blur, occlusion, and dramatic pose changes. For these action sequences, the dataset is accompanied by multi-source reference images, including anime characters, half-body portraits, transgender/cross-style figures, and pose images significantly different from the actions, to simulate common problems in real-world applications such as spatial inconsistencies and temporal discontinuities.