66 citations · 119 across the 15 of their papers we have counts for
15 papers
BiTDiff: Fine-Grained 3D Conducting Motion Generation via BiMamba-Transformer Diffusion
Tianzhi Jia, Kaixing Yang, Xiaole Yang +4
3D conducting motion generation aims to synthesize fine-grained conductor motions from music, with broad potential in music education, virtual performance, digital human animation,…
Frequency-Aware Deepfake Detection: Improving Generalizability through Frequency Space Learning
Chuangchuang Tan, Yao Zhao, Shikui Wei +3
This research addresses the challenge of developing a universal deepfake detector that can effectively identify unseen deepfake images despite limited training data. Existing frequ…
Learning Invariant Inter-pixel Correlations for Superpixel Generation
Sen Xu, Shikui Wei, Tao Ruan +1
Deep superpixel algorithms have made remarkable strides by substituting hand-crafted features with learnable ones. Nevertheless, we observe that existing deep superpixel methods, s…
Structure-Preserving Physics-Informed Neural Networks With Energy or Lyapunov Structure
Haoyu Chu, Yuto Miyatake, Wenjun Cui +2
Recently, there has been growing interest in using physics-informed neural networks (PINNs) to solve differential equations. However, the preservation of structure, such as energy…
Rethinking the Up-Sampling Operations in CNN-based Generative Network for Generalizable Deepfake Detection
Chuangchuang Tan, Huan Liu, Yao Zhao +4
Recently, the proliferation of highly realistic synthetic images, facilitated through a variety of GANs and Diffusions, has significantly heightened the susceptibility to misuse. W…
Lyapunov-Stable Deep Equilibrium Models
Haoyu Chu, Shikui Wei, Ting Liu +2
Deep equilibrium (DEQ) models have emerged as a promising class of implicit layer models, which abandon traditional depth by solving for the fixed points of a single nonlinear laye…