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Tevior
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KV-Control

PyTorch
motion-generation
text-to-motion
humanml3d
controllable-generation
kv-control
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KV-Control
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---
license: mit
library_name: pytorch
tags:
  - motion-generation
  - text-to-motion
  - humanml3d
  - controllable-generation
  - kv-control
pipeline_tag: text-to-motion
---

# KV-Control (T-Concat v4 backbone)

Sparse-keyframe, multi-joint controllable text-to-motion generation. The
repository at [github.com/Tevior/KV-Control](https://github.com/Tevior/KV-Control)
contains the full training and inference code.

## What is here

| Path | Content | Size |
|---|---|---|
| `base_t_concat_v4/model/net_best_fid.tar` | Pre-trained T-Concat v4 masked-transformer base (the paper main backbone) | 168 MB |
| `kv_control/model/net_best_kps.tar`       | KV-Control adapter trained on the base above | 520 MB |
| `vqvae/net_best_fid.pth`                  | Part-aware VQ-VAE tokenizer (128 codes × 6 parts) | 236 MB |
| `vqvae/skeleton_partition.json`           | Skeleton partition for the part-aware VQ | 1 KB |
| `stats/{mean,std}.npy`                    | Normalization stats matching the released VQ | 4 KB |
| `clip/ViT-B-32.pt`                        | OpenAI CLIP ViT-B/32 visual + text encoder | 336 MB |
| `t2m/Comp_v6_KLD005/opt.txt + meta/`      | Frozen evaluation encoder config & stats | 3 KB |
| `t2m/text_mot_match/model/finest.tar`     | Pre-trained text-motion eval encoder (Guo et al., 2022) | 235 MB |
| `t2m/length_estimator/model/finest.tar`   | Pre-trained motion-length predictor | 1.7 MB |
| `aux/body_models/`                        | SMPL neutral mesh + face / J_regressor (SMPL license) | 234 MB |
| `aux/glove/`                              | Vocab files for the length estimator | 10 MB |

## How to use

```bash
git clone https://github.com/Tevior/KV-Control.git
cd KV-Control
bash scripts/download_checkpoints.sh   # populates checkpoints/, aux/ → glove/, body_models/
```

Refer to the GitHub README for installation and quick-start commands.

## Licenses

* Our weights (`base_t_concat_v4`, `kv_control`, `vqvae`, `stats`) — **MIT**.
* CLIP ViT-B/32 — released by OpenAI under MIT.
* SMPL body model under `aux/body_models/` — original SMPL license (research-only).
* Text-motion eval encoder / length estimator under `t2m/` — re-distributed
  from the HumanML3D / Guo et al. 2022 release for reproducibility.

## Citation

```bibtex
@article{kvcontrol2026,
  title  = {KV-Control: Sparse-Keyframe Multi-Joint Text-to-Motion Generation},
  author = {... (under review) ...},
  year   = {2026},
}
```