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3D Group Activity Generation

We provide the 3D group activity dataset, M3Act3D, as well as relevant supporting scripts for data visualization, MDM+IFormer baseline, and evaluation.

Requirements

  • Python 3.9
  • FFMPEG

Install packages:

pip install -r requirements.txt

Preparation

  1. Prepare 3D dataset:

    • Download M3Act3D dataset and put all *.h5 files under current directory (gag/).

  2. Download model checkpoints: (TBD)

M3Act3D Dataset

The h5 data contains simulations of all 6 group activities. The length of each simulation clip is 150 frames, in 30 FPS.

To load the motions given a h5file and the clip index (idx), use the following code snippet:

import h5py

with h5py.File(path_to_h5_file, "r") as h5:
    keys = list(h5.keys())
    idx = 0  # ID of simulation clips

    rot6d = h5[keys[idx]]["6d_rotations"][:]  # 6d rotation representation
    # shape: (150, num_people, num_joints, 6)

    quat = h5[keys[idx]]["quaternions"][:]  # quaternions representation
    # shape: (150, num_people, num_joints, 4)

    wpos = h5[keys[idx]]["w_positions"][:]  # world-space positions
    # shape: (150, num_people, num_joints, 3)

    rot6d = h5[keys[idx]]["bone_lengths"][:]  # bone lengths
    # shape: (num_people, num_bones)

    group_id = h5[keys[idx]]["group_id"][()]  # group class (int)
    group_name = h5[keys[idx]]["group_name"][()]  # group name (str)

    action_id = h5[keys[idx]]["action_id"][:]  # action classes
    # shape: (150, num_people)

    ACTIONS = { 0: 'Idle',
                1: 'Walk',
                2: 'Text',
                3: 'Talk',
                4: 'Wave',
                5: 'Point',
                6: 'Dance',
                7: 'Run',
                8: 'Sit',
                9: 'Fight',
                10: 'Box',
                11: 'Salute',
                12: 'Handshake',
                }

Stick Figure Visualization

python skeleton_visualize.py

Resulting videos will be saved to results/ folder.

SMPL Visualization

TBD

Inference

TBD

Training

TBD