4 citations · 5 across the 5 of their papers we have counts for
6 papers
Graph Navier Stokes Networks
Zexing Zhao, Guangsi Shi, Yu Gong +4
Graph Neural Networks (GNNs) have emerged as a cornerstone of deep learning, with most existing methods rooted in graph signal processing and diffusion equations to model message p…
HOP: Heterogeneous Topology-based Multimodal Entanglement for Co-Speech Gesture Generation
Hongye Cheng, Tianyu Wang, Guangsi Shi +2
Co-speech gestures are crucial non-verbal cues that enhance speech clarity and expressiveness in human communication, which have attracted increasing attention in multimodal resear…
The Curse of Conditions: Analyzing and Improving Optimal Transport for Conditional Flow-Based Generation
Ho Kei Cheng, Alexander Schwing
Minibatch optimal transport coupling straightens paths in unconditional flow matching. This leads to computationally less demanding inference as fewer integration steps and less co…
MMAudio: Taming Multimodal Joint Training for High-Quality Video-to-Audio Synthesis
Ho Kei Cheng, Masato Ishii, Akio Hayakawa +3
We propose to synthesize high-quality and synchronized audio, given video and optional text conditions, using a novel multimodal joint training framework MMAudio. In contrast to si…
Putting the Object Back into Video Object Segmentation
Ho Kei Cheng, Seoung Wug Oh, Brian Price +2
We present Cutie, a video object segmentation (VOS) network with object-level memory reading, which puts the object representation from memory back into the video object segmentati…
Tracking Anything with Decoupled Video Segmentation
Ho Kei Cheng, Seoung Wug Oh, Brian Price +2
Training data for video segmentation are expensive to annotate. This impedes extensions of end-to-end algorithms to new video segmentation tasks, especially in large-vocabulary set…