Papers Multi-Person Pose forecasting
“Multi-Person Pose forecasting” 태그가 달린 논문 9편 · 필터 해제
Social-MAE: Social Masked Autoencoder for Multi-person Motion Representation Learning
For a complete comprehension of multi-person scenes, it is essential to go beyond basic tasks like detection and tracking. Higher-level tasks, such as understanding the interactions and social activities among individual…
Action UnderstandingDecoderMulti-Person Pose forecastingRepresentation LearningPGformer: Proxy-Bridged Game Transformer for Multi-Person Highly Interactive Extreme Motion Prediction
Multi-person motion prediction is a challenging task, especially for real-world scenarios of highly interacted persons. Most previous works have been devoted to studying the case of weak interactions (e.g., walking toget…
motion predictionMulti-Person Pose forecastingBest Practices for 2-Body Pose Forecasting
The task of collaborative human pose forecasting stands for predicting the future poses of multiple interacting people, given those in previous frames. Predicting two people in interaction, instead of each separately, pr…
Human Pose ForecastingMotion Forecastingmotion predictionMulti-Person Pose forecastingTrajectory-Aware Body Interaction Transformer for Multi-Person Pose Forecasting
Multi-person pose forecasting remains a challenging problem, especially in modeling fine-grained human body interaction in complex crowd scenarios. Existing methods typically represent the whole pose sequence as a tempor…
Multi-Person Pose forecastingSoMoFormer: Multi-Person Pose Forecasting with Transformers
Human pose forecasting is a challenging problem involving complex human body motion and posture dynamics. In cases that there are multiple people in the environment, one's motion may also be influenced by the motion and …
Human Pose Forecastingmotion predictionMulti-Person Pose forecastingTime Series AnalysisBack 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 results, however, they rely on deep le…
Human motion predictionHuman Pose Forecastingmotion predictionMulti-Person Pose forecastingMulti-Person 3D Motion Prediction with Multi-Range Transformers
We propose a novel framework for multi-person 3D motion trajectory prediction. Our key observation is that a human's action and behaviors may highly depend on the other persons around. Thus, instead of predicting each hu…
Decodermotion predictionMulti-Person Pose forecastingPrediction+1Multi-Person Extreme Motion Prediction
Human motion prediction aims to forecast future poses given a sequence of past 3D skeletons. While this problem has recently received increasing attention, it has mostly been tackled for single humans in isolation. In th…
Human motion predictionmotion predictionMulti-Person Pose forecastingPose Prediction+1Learning Trajectory Dependencies for Human Motion Prediction
Human motion prediction, i.e., forecasting future body poses given observed pose sequence, has typically been tackled with recurrent neural networks (RNNs). However, as evidenced by prior work, the resulted RNN models su…
Human motion predictionHuman Pose Forecastingmotion predictionMulti-Person Pose forecasting+1