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Parking Spot Occupancy Recognition

This repository contains the models and evaluations associated with the paper Toward Parking Spot Occupancy Recognition: A Self-Supervised Approach.

TipoOtherVersãoRevision 31901ecCnota

Fonte do modelo

Tipo
Other
Tamanho do arquivo
90,0–107 MB
Versão
vRevision 31901ec
Atualizado
17 de set. de 2026
Downloads
0
Fonte
Hugging Face

Descrição da fonte

Toward Parking Spot Occupancy Recognition: A Self-Supervised Approach

This repository contains the models and evaluations associated with the paper Toward Parking Spot Occupancy Recognition: A Self-Supervised Approach.

The official code is available on GitHub: Parking-Spot-Occupancy-Recognition.

Overview

This work proposes a self-supervised approach for parking spot occupancy recognition that requires no labeled samples from the target parking lot. The training pipeline consists of three stages:

  1. Stage 1: Self-supervised pretraining using the SimCLR framework on generic data (ImageNet).
  2. Stage 2: Self-supervised fine-tuning on parking spot occupancy data (PKLot, CNRPark-EXT, and PLds) to adapt to specific characteristics of parking spot images.
  3. Stage 3: Supervised fine-tuning on parking spot occupancy data to refine the model's ability to classify parking spot occupancy accurately.

Evaluation

The models are evaluated under a leave-one-out cross-environment protocol on three public datasets: PKLot, CNRPark-EXT, and PLds. For more details on the performance and implementation of the Strong General Model and Specialized Model, please refer to the paper.

Citation

@article{kujavski2026toward,
  title={Toward Parking Spot Occupancy Recognition: A Self-Supervised Approach},
  author={Kujavski, Luan Marko and Laroca, Rayson and de Almeida, Paulo Lisboa},
  journal={arXiv preprint arXiv:2606.20886},
  year={2026}
}

Fontes

1 fonte
Hugging FacePrimárioVersão 31901ec1bee3650f943b3c47f4ffe1569565ca4b
huggingface.co/LoanMaikon/Parking-Spot-Occupancy-Recognition/tree/31901ec1bee3650f943b3c47f4ffe1569565ca4b

Verificado 2 de set.

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Artefatos de modelo

41 artefatos

general/cnr_plds_test_pklot/execution_1/model.pth

pth · 107 MB · SHA-256 20a86c4f645b…c46f · Hugging Face

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general/pklot_cnr_test_plds/execution_1/model.pth

pth · 107 MB · SHA-256 c552be107945…a8ce · Hugging Face

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general/pklot_cnr_test_plds/execution_1/supervised/model.pth

pth · 90,0 MB · SHA-256 f45ad4231f26…2a4f · Hugging Face

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general/pklot_plds_test_cnr/execution_1/model.pth

pth · 107 MB · SHA-256 116d7a20efd6…02fb · Hugging Face

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general/pklot_plds_test_cnr/execution_1/supervised/model.pth

pth · 90,0 MB · SHA-256 e90beea82d3a…c1e8 · Hugging Face

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selfsupervised/cnr_plds_test_pklot/execution_1/model.pth

pth · 90,0 MB · SHA-256 921a0d7ded33…d20a · Hugging Face

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selfsupervised/pklot_cnr_test_plds/execution_1/model.pth

pth · 90,0 MB · SHA-256 19ca27f109e5…f26e · Hugging Face

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selfsupervised/pklot_plds_test_cnr/execution_1/model.pth

pth · 90,0 MB · SHA-256 3c3f02fb1478…9d70 · Hugging Face

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specialized/camera1/execution_1/model.pth

pth · 107 MB · SHA-256 75257745e9b4…548c · Hugging Face

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specialized/camera1/execution_1/supervised/model.pth

pth · 90,0 MB · SHA-256 ba290875544a…dd64 · Hugging Face

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specialized/camera2/execution_1/model.pth

pth · 107 MB · SHA-256 f31864e7d702…76d9 · Hugging Face

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specialized/camera2/execution_1/supervised/model.pth

pth · 90,0 MB · SHA-256 3c3bfe8ccd51…783f · Hugging Face

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specialized/camera3/execution_1/model.pth

pth · 107 MB · SHA-256 33c952ac1725…bed1 · Hugging Face

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specialized/camera3/execution_1/supervised/model.pth

pth · 90,0 MB · SHA-256 3c1af9e82116…838a · Hugging Face

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specialized/camera4/execution_1/model.pth

pth · 107 MB · SHA-256 8419bcc9a6bc…ce46 · Hugging Face

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specialized/camera4/execution_1/supervised/model.pth

pth · 90,0 MB · SHA-256 d3b37476e8b1…521a · Hugging Face

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specialized/camera5/execution_1/model.pth

pth · 107 MB · SHA-256 62033d1c17aa…02b1 · Hugging Face

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specialized/camera5/execution_1/supervised/model.pth

pth · 90,0 MB · SHA-256 4bdafe42cf84…f013 · Hugging Face

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specialized/camera6/execution_1/model.pth

pth · 107 MB · SHA-256 3d8e3a618e16…df9a · Hugging Face

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specialized/camera6/execution_1/supervised/model.pth

pth · 90,0 MB · SHA-256 b17692fa9b67…0cce · Hugging Face

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specialized/camera7/execution_1/model.pth

pth · 107 MB · SHA-256 79134a9d4e6d…6d69 · Hugging Face

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specialized/camera7/execution_1/supervised/model.pth

pth · 90,0 MB · SHA-256 bc75aae7c4fb…52ac · Hugging Face

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specialized/camera8/execution_1/model.pth

pth · 107 MB · SHA-256 feb14e79b25e…34ad · Hugging Face

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specialized/camera8/execution_1/supervised/model.pth

pth · 90,0 MB · SHA-256 85ae62afc825…8745 · Hugging Face

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specialized/camera9/execution_1/model.pth

pth · 107 MB · SHA-256 8573b3ff134f…397f · Hugging Face

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specialized/camera9/execution_1/supervised/model.pth

pth · 90,0 MB · SHA-256 d4e7d57c9c14…35b7 · Hugging Face

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specialized/isshk/execution_1/model.pth

pth · 107 MB · SHA-256 284223a26efa…d006 · Hugging Face

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specialized/isshk/execution_1/supervised/model.pth

pth · 90,0 MB · SHA-256 81119a2b1327…215e · Hugging Face

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specialized/pucpr/execution_1/model.pth

pth · 107 MB · SHA-256 174b3510096a…242a · Hugging Face

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specialized/pucpr/execution_1/supervised/model.pth

pth · 90,0 MB · SHA-256 4a6a4d1124f7…bdfb · Hugging Face

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specialized/qridr/execution_1/model.pth

pth · 107 MB · SHA-256 7d4ad7784875…ffe7 · Hugging Face

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specialized/qridr/execution_1/supervised/model.pth

pth · 90,0 MB · SHA-256 a23bf6bd1f4e…c5e6 · Hugging Face

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specialized/ufpr04/execution_1/model.pth

pth · 107 MB · SHA-256 285ea1596ad2…73a2 · Hugging Face

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specialized/ufpr04/execution_1/supervised/model.pth

pth · 90,0 MB · SHA-256 0d43a12aaee0…c96f · Hugging Face

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specialized/ufpr05/execution_1/model.pth

pth · 107 MB · SHA-256 fdf08d5dc456…453c · Hugging Face

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specialized/ufpr05/execution_1/supervised/model.pth

pth · 90,0 MB · SHA-256 e670f32bd677…a5d7 · Hugging Face

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specialized/vxusd,vmlix/execution_1/model.pth

pth · 107 MB · SHA-256 70d10af3a4c2…a6aa · Hugging Face

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specialized/vxusd,vmlix/execution_1/supervised/model.pth

pth · 90,0 MB · SHA-256 0f317bea0c82…61cf · Hugging Face

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supervised/cnr_plds_test_pklot/execution_1/model.pth

pth · 90,0 MB · SHA-256 69078386e91b…185e · Hugging Face

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supervised/pklot_cnr_test_plds/execution_1/model.pth

pth · 90,0 MB · SHA-256 7aade2512750…514a · Hugging Face

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supervised/pklot_plds_test_cnr/execution_1/model.pth

pth · 90,0 MB · SHA-256 29ec087b9434…af29 · Hugging Face

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Trechos de fonte

2 trechos

--- license: apache-2.0 pipeline_tag: image-classification --- # Toward Parking Spot Occupancy Recognition: A Self-Supervised Approach This repository contains the models and evaluations associated with the paper [Toward Parking Spot Occupancy Recognition: A Self-Supervised Approach](https://huggingface.co/papers/2606.20886). The official code is available on GitHub: [Parking-Spot-Occupancy-Recognition](https://github.com/LoanMaikon/Parking-Spot-Occupancy-Recognition). ## Overview This work proposes a self-supervised approach for parking spot occupancy recognition that requires no labeled samples from the target parking lot. The training pipeline consists of three stages: 1. **Stage 1: Self-supervised pretraining** using the SimCLR framework on generic data (ImageNet). 2. **Stage 2: Self-supervised fine-tuning** on parking spot occupancy data (PKLot, CNRPark-EXT, and PLds) to adapt to specific characteristics of parking spot images. 3. **Stage 3: Supervised fine-tuning** on parking spot occupancy data to refine the model's ability to classify parking spot occupancy accurately. ## Evaluation The models are evaluated under a leave-one-out cross-environment protocol on three public datasets: PKLot, CNRPark-EXT, and PLds. For more details on the performance and implementation of the Strong General Model and Specialized Model, please refer to the [paper](https://huggingface.co/papers/2606.20886). ## Citation ```bibtex @article{kujavski2026toward, title={Toward Parking Spot Occupancy Recognition: A Self-Supervised Approach}, author={Kujavski, Luan Marko and Laroca, Rayson and de Almeida, Paulo Lisboa}, journal={arXiv preprint arXiv:2606.20886}, year={2026} } ```

Source context: 0 downloads · 1 likes · Pipeline image-classification · Repo LoanMaikon/Parking-Spot-Occupancy-Recognition