metadata
license: mit
tags:
- text-to-motion
- motion-generation
- trajectory-control
- humanml3d
library_name: pytorch
KV-Control (C-Concat substrate) — pretrained weights
Pretrained weights for KV-Control, a parameter-efficient attention-side key/value injection adapter for trajectory-controlled text-to-motion generation on a frozen PartVQ + C-Concat masked-motion (MaskGIT-style) backbone.
Code: https://github.com/CHDTevior/kvcontrol-c-concat
Download the whole tree into ./pretrained/ of the code repo (bash scripts/download_weights.sh).
Files
| Path | Description |
|---|---|
partvq/vq_net_best_fid.pth + partvq/skeleton_partition.json |
Frozen part-aware VQ tokenizer + skeleton partition (required substrate) |
normalization/mean.npy, normalization/std.npy |
263-dim HumanML3D feature statistics |
c_concat_base/net_best_fid.tar |
Frozen C-Concat masked-motion backbone |
kv_control/net_best_fid.tar |
KV-Control trajectory adapter (best FID) |
kv_control/net_best_top3.tar |
KV-Control trajectory adapter (best Top-3) |
Results (HumanML3D test, single-joint pelvis trajectory, 5-repeat mean ± 95% CI)
| Protocol | FID | Top-3 | KPS (cm) |
|---|---|---|---|
| M2 (MaskControl-matched TTT) | 0.093 ± 0.011 | 0.795 ± 0.011 | 1.10 ± 0.01 |
| M3 (+ dynamic refinement) | 0.096 ± 0.011 | 0.793 ± 0.006 | 0.96 ± 0.01 |
Citation
Anonymous AAAI-2027 submission under review; author information withheld.
License
MIT (weights and code). Please also honor the licenses of HumanML3D and upstream projects (MoMask / MaskControl / OpenAI CLIP).