Error code:   JWTInvalidSignature
Exception:    InvalidSignatureError
Message:      Signature verification failed
Traceback:    Traceback (most recent call last):
                File "/src/libs/libapi/src/libapi/jwt_token.py", line 286, in validate_jwt
                  decoded = jwt.decode(
                      jwt=token,
                  ...<2 lines>...
                      options=options,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 368, in decode
                  decoded = self.decode_complete(
                      jwt,
                  ...<8 lines>...
                      leeway=leeway,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 265, in decode_complete
                  decoded = self._jws.decode_complete(
                      jwt,
                  ...<3 lines>...
                      detached_payload=detached_payload,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 270, in decode_complete
                  self._verify_signature(
                  ~~~~~~~~~~~~~~~~~~~~~~^
                      signing_input,
                      ^^^^^^^^^^^^^^
                  ...<4 lines>...
                      options=merged_options,
                      ^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 417, in _verify_signature
                  raise InvalidSignatureError("Signature verification failed")
              jwt.exceptions.InvalidSignatureError: Signature verification failed

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

YAML Metadata Warning:The task_categories "video-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other

YAML Metadata Warning:The task_categories "computer-vision" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other

🎵 MACE-Dance Dataset

MACE-Dance is a large-scale dataset for music-driven dance video generation, released with our SIGGRAPH 2026 paper:

MACE-Dance: Motion-Appearance Cascaded Experts for Music-Driven Dance Video Generation

It is designed to support research on generating dance videos that are both:

🕺 kinematically plausible
🎨 visually coherent
🎼 well aligned with music

✨ Overview

The dataset contains approximately:

70K dance video clips
5–10 seconds per clip
116 hours in total
20+ dance genres

The data is curated from two complementary sources:

1. Motion-centric subset

Derived from FineDance
Front-view rendered dance videos from 3D motion sequences
Focused on professional dance motion quality

2. Appearance-centric subset

Collected from high-engagement internet dance videos
Focused on visual appearance diversity and realism

This design helps benchmark both motion quality and appearance quality in music-driven dance video generation.

📂 Folder Structure

MACE-Dance/
├── Appearance/
└── Kinematic/

The exact file organization may vary depending on the released version.

🧹 Data Curation

For the in-the-wild subset, we apply a multi-stage cleaning pipeline:

✂️ shot boundary detection
🚶 motion filtering
🧍 single-person filtering
⏱️ clip segmentation into 5–10 second windows

This improves data quality for the music-driven dance generation task.

🎯 Intended Usage

This dataset is intended for research on:

music-driven dance video generation
music-driven 3D dance generation
pose-driven / motion-driven human animation
motion and appearance evaluation

⚠️ Notes

This dataset is released for research purposes only.
Please ensure your use complies with the corresponding license and platform policies.
Some samples may originate from internet videos and are curated for academic research.

📚 Citation

If you find this dataset useful, please cite:

@article{yang2026macedance,
  title={MACE-Dance: Motion-Appearance Cascaded Experts for Music-Driven Dance Video Generation},
  author={Yang, Kaixing and Zhu, Jiashu and Tang, Xulong and Peng, Ziqiao and Zhang, Xiangyue and Wang, Puwei and Wu, Jiahong and Chu, Xiangxiang and Liu, Hongyan and He, Jun},
  journal={ACM Transactions on Graphics (SIGGRAPH 2026)},
  year={2026}
}

Downloads last month: 87

Total file size:

195 GB