Video-Text-to-Text
Transformers
Safetensors
qwen3_vl
image-text-to-text
qwen3-vl
video
motion-analysis
motion-quality-assessment
Instructions to use JohnZhan/MotionInsight-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JohnZhan/MotionInsight-8B with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("JohnZhan/MotionInsight-8B") model = AutoModelForMultimodalLM.from_pretrained("JohnZhan/MotionInsight-8B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
MotionInsight-8B
This is the released multidim-all/checkpoint-5500 for MotionInsight:
Diagnosing Object Motion Deficiencies in Generated Videos.
The model consumes sampled RGB frames, target-object motion features from SAM3 and CoTracker3, and camera motion from VIPE. It predicts diagnostic reasoning and three motion-quality scores.
Use this checkpoint with the code and custom Qwen3-VL implementation from:
https://github.com/JohnZhan2023/MotionInsight
hf download JohnZhan/MotionInsight-8B \
--local-dir checkpoints/MotionInsight-8B
python scripts/patch_transformers.py
python inference.py --help
The VidMotion dataset, videos, and annotations are not distributed.
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