Contact-aware human motion forecasting
W Mao, RI Hartley, M Salzmann - Advances in Neural …, 2022 - proceedings.neurips.cc
In this paper, we tackle the task of scene-aware 3D human motion forecasting, which
consists of predicting future human poses given a 3D scene and a past human motion. A key …
consists of predicting future human poses given a 3D scene and a past human motion. A key …
Spatio-temporal branching for motion prediction using motion increments
Human motion prediction (HMP) has emerged as a popular research topic due to its diverse
applications. Traditional methods rely on hand-crafted features and machine learning …
applications. Traditional methods rely on hand-crafted features and machine learning …
Weakly-supervised action transition learning for stochastic human motion prediction
W Mao, M Liu, M Salzmann - Proceedings of the IEEE/CVF …, 2022 - openaccess.thecvf.com
We introduce the task of action-driven stochastic human motion prediction, which aims to
predict multiple plausible future motions given a sequence of action labels and a short …
predict multiple plausible future motions given a sequence of action labels and a short …
DMS-GCN: dynamic mutiscale spatiotemporal graph convolutional networks for human motion prediction
Human motion prediction is an important and challenging task in many computer vision
application domains. Recent work concentrates on utilizing the timing processing ability of …
application domains. Recent work concentrates on utilizing the timing processing ability of …
Scene-aware Human Motion Forecasting via Mutual Distance Prediction
C Xing, W Mao, M Liu - arXiv preprint arXiv:2310.00615, 2023 - arxiv.org
In this paper, we tackle the problem of scene-aware 3D human motion forecasting. A key
challenge of this task is to predict future human motions that are consistent with the scene …
challenge of this task is to predict future human motions that are consistent with the scene …
Adversarial refinement network for human motion prediction
Human motion prediction aims to predict future 3D skeletal sequences by giving a limited
human motion as inputs. Two popular methods, recurrent neural networks and feed-forward …
human motion as inputs. Two popular methods, recurrent neural networks and feed-forward …
Context-based Interpretable Spatio-Temporal Graph Convolutional Network for Human Motion Forecasting
Human motion prediction is still an open problem extremely important for autonomous
driving and safety applications. Due to the complex spatiotemporal relation of motion …
driving and safety applications. Due to the complex spatiotemporal relation of motion …
Spatial–temporal modeling for prediction of stylized human motion
Human motion prediction refers to forecasting human motion in the future given a past
motion sequence, which has significant applications in human tracking, automatic motion …
motion sequence, which has significant applications in human tracking, automatic motion …
Back to mlp: A simple baseline for human motion prediction
This paper tackles the problem of human motion prediction, consisting in forecasting future
body poses from historically observed sequences. State-of-the-art approaches provide good …
body poses from historically observed sequences. State-of-the-art approaches provide good …
Human motion prediction using manifold-aware wasserstein gan
B Chopin, N Otberdout, M Daoudi… - 2021 16th IEEE …, 2021 - ieeexplore.ieee.org
Human motion prediction aims to forecast future human poses given a prior pose sequence.
The discontinuity of the predicted motion and the performance deterioration in long-term …
The discontinuity of the predicted motion and the performance deterioration in long-term …