Summary of Ds Myolo: a Reliable Object Detector Based on Ssms For Driving Scenarios, by Yang Li and Jianli Xiao
DS MYOLO: A Reliable Object Detector Based on SSMs for Driving Scenarios
by Yang Li, Jianli Xiao
First submitted to arxiv on: 2 Sep 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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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 novel object detector, DS MYOLO, which leverages global receptive fields to enhance the performance of deep learning-based real-time object detection. Building upon recent advancements in Transformer-based self-attention mechanisms and efficient channel attention convolutions (ECAConv), the proposed detector integrates these innovations with simplified selective scanning fusion blocks (SimVSS Blocks). This architecture is designed to maintain low computational complexity while achieving competitive performance among similarly scaled YOLO series real-time object detectors. The paper presents extensive experiments on two driving scenarios datasets, demonstrating the potential and advantage of DS MYOLO in enhancing the safety of advanced driver-assistance systems. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper creates a new kind of camera that can quickly find objects in real-time, like cars or people. This is important because it helps make self-driving cars safer. The current best cameras use something called CNNs (a type of computer algorithm), but they have some limitations. Some other researchers came up with a way to improve these cameras using Transformers (another type of computer algorithm). However, this new method has some drawbacks too. This paper takes inspiration from the good parts of both ideas and creates a new camera that combines the best of both worlds. The authors tested their camera on two different types of scenarios and found that it works really well. |
Keywords
» Artificial intelligence » Attention » Deep learning » Object detection » Self attention » Transformer » Yolo
