5 papers
Trajectory-Level Automatic Curriculum Learning for Legged Locomotion on Unstructured Terrain
Rocky Liu, Tengyu Liu, Baoxiong Jia +4
Training locomotion policies for complex unstructured terrain requires a curriculum to avoid early exploration failures. However, since unstructured terrain lacks explicit difficul…
MADB: A Large-Scale Music Aesthetics Dataset with Professional and Multi-Dimensional Annotations
Sirui Zhang, Tianle Wang, Xinyi Tong +8
Music aesthetic assessment is a challenging yet underexplored problem, requiring models to capture fine-grained, multi-dimensional human perceptual judgments. Progress in this area…
Video Echoed in Music: Semantic, Temporal, and Rhythmic Alignment for Video-to-Music Generation
Xinyi Tong, Yiran Zhu, Jishang Chen +9
Video-to-Music generation seeks to generate musically appropriate background music that enhances audiovisual immersion for videos. However, current approaches suffer from two criti…
Discovering "Words" in Music: Unsupervised Learning of Compositional Sparse Code for Symbolic Music
Tianle Wang, Sirui Zhang, Xinyi Tong +12
This paper presents an unsupervised machine learning algorithm that identifies recurring patterns -- referred to as ``music-words'' -- from symbolic music data. These patterns are…
Learning Uniformly Distributed Embedding Clusters of Stylistic Skills for Physically Simulated Characters
Nian Liu, Libin Liu, Zilong Zhang +6
Learning natural and diverse behaviors from human motion datasets remains challenging in physics-based character control. Existing conditional adversarial models often suffer from…