Summary of A Lightweight Modular Framework For Low-cost Open-vocabulary Object Detection Training, by Bilal Faye et al.
A Lightweight Modular Framework for Low-Cost Open-Vocabulary Object Detection Training
by Bilal Faye, Binta Sow, Hanane Azzag, Mustapha Lebbah
First submitted to arxiv on: 20 Aug 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper proposes a lightweight framework for open-vocabulary object detection, which redefines the traditional approach by incorporating region-level vision-language pre-training. The goal is to overcome the limitations of existing methods, which are often constrained by a fixed vocabulary of objects. The authors introduce Lightweight MDETR (LightMDETR), an optimized version of MDETR that reduces computational costs while preserving accuracy. This is achieved by freezing the MDETR backbone and training only the Universal Projection module, which bridges vision and language representations. The learnable modality token parameter allows seamless switching between modalities. Evaluations on phrase grounding, referring expression comprehension, and segmentation tasks show that LightMDETR outperforms several state-of-the-art methods in terms of accuracy. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps us better understand computers by teaching them to recognize objects in pictures. Right now, computers are good at recognizing a limited number of things, but they can’t identify everything. To fix this, the authors developed a new way for computers to learn about different types of objects. This new method is faster and more efficient than previous methods, which means it can process more information without getting slow or tired. The results show that this new method is better at recognizing objects in pictures than other current methods. |
Keywords
» Artificial intelligence » Grounding » Object detection » Token
