Going Denser with Open-Vocabulary Part Segmentation

Publication date: 18 May 2023

Topic: Object detection

Paper: https://arxiv.org/pdf/2305.11173v1.pdf

GitHub: https://github.com/facebookresearch/vlpart

Denoscription:

Object detection has been expanded from a limited number of categories to open vocabulary. Moving forward, a complete intelligent vision system requires understanding more fine-grained object denoscriptions, object parts. In this work, we propose a detector with the ability to predict both open-vocabulary objects and their part segmentation. This ability comes from two designs:

🔹 We train the detector on the joint of part-level, object-level and image-level data.
🔹 We parse the novel object into its parts by its dense semantic correspondence with the base object.

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In Data Science you can find multiple data distributions...

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🚀 Deep Learning CNN Project: Cat vs Dog Classification

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