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---
# CaMiT: Car Models in Time
**CaMiT (Car Models in Time)** is a large-scale, fine-grained, time-aware dataset of car images collected from Flickr. It is designed to support research on temporal adaptation in visual models, continual learning, and time-aware generative modeling.
## Dataset Highlights
- **Labeled Subset**:
- 787,000 samples
- 190 car models
- 2007–2023
- **Unlabeled Pretraining Subset**:
- 5.1 million samples
- 2005–2023
- **Metadata** includes:
- Image URLs (not the images themselves)
- Upload time
- Bounding boxes
- Tags and licensing
- Face detections
- Car detection scores and class information
All images are **linked** (not redistributed) using Flickr metadata to respect copyright compliance, in line with LAION and DataComp datasets.
## Tasks Supported
- **Time-aware fine-grained classification**
- **Time-incremental continual learning**
- **In-domain static and incremental pretraining**
- **Time-aware image generation**
## Example Use Cases
- Evaluating representation drift over time
- Training classifiers that generalize across time periods
- Studying model degradation and adaptation across years
- Conditioning generation models on temporal context
## Related Resource
A separate dataset containing precomputed **image embeddings**, categorized by **car class** and **year**, is available here:
👉 [CaMiT Embeddings](https://huggingface.co/datasets/fredericlin/CaMiT-embeddings)
## License
CC BY-NC-SA 4.0 – for non-commercial research purposes only. |