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AnimajSAS/AIS_BI_LSTM_v0
AIS_BI_LSTM_v0 is a machine learning model from AnimajSAS. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
This is the AIS-BiLSTM model accompanying the paper:
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Updated May 7, 2026
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From the Hugging Face model README
This is the AIS-BiLSTM model accompanying the paper:
https://arxiv.org/abs/2605.02742
Raël et al., "Adaptive Interpolation-Synthesis for Motion In-Betweening on Keyframe-Based Animation", SIGGRAPH 2026 Conference Papers (2026)
The AIS-BiLSTM model takes as input a tensor of shape N×(D+1), where N is the number of frames in the sequence and D=596 is the pose dimension. The K input keyposes are placed at their target frame indices in the first D channels, with all other frames zero-filled. The last channel is a binary mask flagging the K keypose positions. The model predicts the full N×D pose sequence.
| Property | Value |
|---|---|
| Framework | PyTorch Lightning |
| Checkpoint format | .safetensors |
| Input | Masked sequence of shape N×(D+1) |
| Output | Completed sequence of shape N×D |
| Pose dimensionality | D = 596 |
| Training sequence length | N=224 frames (fixed); variable length supported at inference |
| Frame rate | 24 fps |
See the GitHub repository
Trained on the train split of the mib_rig_controllers_values dataset, comprising ~8.1 hours of professionally handcrafted animation at 24 fps.
Evaluated on three test splits of the mib_rig_controllers_values dataset:
| Split | Schedule | Description |
|---|---|---|
test_held_out_algorithmic | DBA | Held-Out set with a deterministic keypose schedule from the domain-based algorithm |
test_held_out_random | Random (r=0.9) | Held-Out set with a random keypose schedule |
test_production | Block | 5 min production data with ground-truth block keyposes |
Apache 2.0