88 citations · 144 across the 12 of their papers we have counts for
12 papers
Action Recognition with Multi-stream Motion Modeling and Mutual Information Maximization
Yuheng Yang, Haipeng Chen, Zhenguang Liu +5
Action recognition has long been a fundamental and intriguing problem in artificial intelligence. The task is challenging due to the high dimensionality nature of an action, as wel…
Analytical Equation of Three-point Correlation Function of Galaxies: to Third Order of Density Perturbation
Shu-Guang Wu, Yang Zhang
Applying functional differentiation to the density field with Newtonian gravity, we obtain the static, nonlinear equation of the three-point correlation function of galaxies, t…
Copy Motion From One to Another: Fake Motion Video Generation
Zhenguang Liu, Sifan Wu, Chejian Xu +4
One compelling application of artificial intelligence is to generate a video of a target person performing arbitrary desired motion (from a source person). While the state-of-the-a…
SYK model with an extra diagonal perturbation: phase transition in the eigenvalue spectrum
Shuang Wu
We study the SYK model with an extra constant source, i.e. a constant matrix or equivalently a diagonal matrix with only one non-zero entry . By using methods from analytic co…
Temporal Feature Alignment and Mutual Information Maximization for Video-Based Human Pose Estimation
Zhenguang Liu, Runyang Feng, Haoming Chen +4
Multi-frame human pose estimation has long been a compelling and fundamental problem in computer vision. This task is challenging due to fast motion and pose occlusion that frequen…
Dual Learning Music Composition and Dance Choreography
Shuang Wu, Zhenguang Li, Shijian Lu +1
Music and dance have always co-existed as pillars of human activities, contributing immensely to the cultural, social, and entertainment functions in virtually all societies. Notwi…
Motion Prediction via Joint Dependency Modeling in Phase Space
Pengxiang Su, Zhenguang Liu, Shuang Wu +3
Motion prediction is a classic problem in computer vision, which aims at forecasting future motion given the observed pose sequence. Various deep learning models have been proposed…
Investigating Pose Representations and Motion Contexts Modeling for 3D Motion Prediction
Zhenguang Liu, Shuang Wu, Shuyuan Jin +4
Predicting human motion from historical pose sequence is crucial for a machine to succeed in intelligent interactions with humans. One aspect that has been obviated so far, is the…
Learning Human Motion Prediction via Stochastic Differential Equations
Kedi Lyu, Zhenguang Liu, Shuang Wu +3
Human motion understanding and prediction is an integral aspect in our pursuit of machine intelligence and human-machine interaction systems. Current methods typically pursue a kin…
Music-to-Dance Generation with Optimal Transport
Shuang Wu, Shijian Lu, Li Cheng
Dance choreography for a piece of music is a challenging task, having to be creative in presenting distinctive stylistic dance elements while taking into account the musical theme…
Deep Dual Consecutive Network for Human Pose Estimation
Zhenguang Liu, Haoming Chen, Runyang Feng +4
Multi-frame human pose estimation in complicated situations is challenging. Although state-of-the-art human joints detectors have demonstrated remarkable results for static images,…
Aggregated Multi-GANs for Controlled 3D Human Motion Prediction
Zhenguang Liu, Kedi Lyu, Shuang Wu +3
Human motion prediction from historical pose sequence is at the core of many applications in machine intelligence. However, in current state-of-the-art methods, the predicted futur…