<p><strong>Yolov4 Vs Yolov3:</strong></p>
<ul>
<li>Yolov3 uses <strong><code>Darknet53</code></strong> as backbone, Yolov4 uses
<strong><code>CSPDarknet53</code></strong> as backbone.</li>
<li>Yolov4 uses <code>PANet</code> as the method of parameter aggregation from different backbone levels for different detector levels, instead of the <code>FPN</code> used in Yolov3.</li>
</ul>
<p>YOLOv4 consists of:</p>
<ol>
<li><strong>Backbone:</strong> CSPDarknet53  (Feature Extraction)</li>
<li><strong>Neck:</strong> Additional module - SPP, PANet [this was not there in Yolov3]</li>
<li><strong>Head:</strong> YOLOv3 (Dense Prediction Block) [This part is same as Yolov3]</li>
</ol>
<p><a href="https://i.stack.imgur.com/xrOwX.png" rel="noreferrer"><img src="https://i.stack.imgur.com/xrOwX.png" alt="Yolov4-arch" /></a></p>
<blockquote>
<p><strong>Neck:</strong> Object detectors developed in recent years often insert some
layers between backbone and head, and these layers are usually used to
collect feature maps from different stages.</p>
</blockquote>
<p>References:</p>
<ul>
<li>Read <a href="https://arxiv.org/pdf/2004.10934.pdf" rel="noreferrer">Yolov4</a> paper in detail</li>
<li>Read <a href="https://medium.com/@jonathan_hui/yolov4-c9901eaa8e61" rel="noreferrer">this</a> article</li>
</ul>
How Yolo 3 is implemented in Yolo 4?
<p>I try to understand the architecture of Yolo4.
It is composed of a backbone, neck, dense prediction and sparse prediction.
Knowing that Yolo 3 has already a backbone, Is Yolo 4 taking all the architecture of Yolo 3 including its backbone or just part of Yolo3 ?</p>
<p>In page number 5 in paper Yolo 4, they've mentioned anchor based for Yolo3</p>
<p>Yolo 4 : <a href="https://arxiv.org/pdf/2004.10934.pdf" rel="noreferrer">https://arxiv.org/pdf/2004.10934.pdf</a></p>
<p>Yolo 3 :<a href="https://pjreddie.com/media/files/papers/YOLOv3.pdf" rel="noreferrer">https://pjreddie.com/media/files/papers/YOLOv3.pdf</a></p>