Papers › Multi-Person Extreme Motion Prediction
Multi-Person Extreme Motion Prediction
Wen Guo, Xiaoyu Bie, Xavier Alameda-Pineda, Francesc Moreno-Noguer
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 this paper, we explore this problem when dealing with humans performing collaborative tasks, we seek to predict the future motion of two interacted persons given two sequences of their past skeletons. We propose a novel cross interaction attention mechanism that exploits historical information of both persons, and learns to predict cross dependencies between the two pose sequences. Since no dataset to train such interactive situations is available, we collected ExPI (Extreme Pose Interaction), a new lab-based person interaction dataset of professional dancers performing Lindy-hop dancing actions, which contains 115 sequences with 30K frames annotated with 3D body poses and shapes. We thoroughly evaluate our cross interaction network on ExPI and show that both in short- and long-term predictions, it consistently outperforms state-of-the-art methods for single-person motion prediction.
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Tasks
Datasets
Introduced by this paper, per the archive.
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Multi-Person Pose forecasting | Expi - common actions split | XIA | Average MPJPE (mm) @ 1000 ms | 238 | #3 of 6 | Archive leaderboard | report |
| Multi-Person Pose forecasting | Expi - common actions split | XIA | Average MPJPE (mm) @ 200 ms | 55 | #3 of 6 | Archive leaderboard | report |
| Multi-Person Pose forecasting | Expi - common actions split | XIA | Average MPJPE (mm) @ 400 ms | 112 | #3 of 6 | Archive leaderboard | report |
| Multi-Person Pose forecasting | Expi - common actions split | XIA | Average MPJPE (mm) @ 600 ms | 162 | #3 of 6 | Archive leaderboard | report |
| Multi-Person Pose forecasting | Expi - unseen actions split | XIA | Average MPJPE (mm) @ 400 ms | 121 | #2 of 5 | Archive leaderboard | report |
| Multi-Person Pose forecasting | Expi - unseen actions split | XIA | Average MPJPE (mm) @ 600 ms | 174 | #2 of 5 | Archive leaderboard | report |
| Multi-Person Pose forecasting | Expi - unseen actions split | XIA | Average MPJPE (mm) @ 800 ms | 218 | #2 of 5 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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