5 citations · 12 across the 6 of their papers we have counts for
6 papers
Physics-constrained Attack against Convolution-based Human Motion Prediction
Chengxu Duan, Zhicheng Zhang, Xiaoli Liu +2
Human motion prediction has achieved a brilliant performance with the help of convolution-based neural networks. However, currently, there is no work evaluating the potential risk…
Rich Action-semantic Consistent Knowledge for Early Action Prediction
Xiaoli Liu, Jianqin Yin, Di Guo +1
Early action prediction (EAP) aims to recognize human actions from a part of action execution in ongoing videos, which is an important task for many practical applications. Most pr…
SDMTL: Semi-Decoupled Multi-grained Trajectory Learning for 3D human motion prediction
Xiaoli Liu, Jianqin Yin
Predicting future human motion is critical for intelligent robots to interact with humans in the real world, and human motion has the nature of multi-granularity. However, most of…
DeepSSM: Deep State-Space Model for 3D Human Motion Prediction
Xiaoli Liu, Jianqin Yin, Huaping Liu +1
Predicting future human motion plays a significant role in human-machine interactions for various real-life applications. A unified formulation and multi-order modeling are two cri…
TrajectoryNet: a new spatio-temporal feature learning network for human motion prediction
Xiaoli Liu, Jianqin Yin, Jin Liu +3
Human motion prediction is an increasingly interesting topic in computer vision and robotics. In this paper, we propose a new 2D CNN based network, TrajectoryNet, to predict future…
PISEP^2: Pseudo Image Sequence Evolution based 3D Pose Prediction
Xiaoli Liu, Jianqin Yin, Huaping Liu +1
Pose prediction is to predict future poses given a window of previous poses. In this paper, we propose a new problem that predicts poses using 3D joint coordinate sequences. Differ…