<p>First, what is YOLOv3 composed of?</p>
<p>YOLOv3 is composed of two parts:</p>
<ol>
<li>Backbone or Feature Extractor --&gt; Darknet53</li>
<li>Head or Detection Blocks --&gt; 53 layers</li>
</ol>
<p>The head is used for (1) bounding box localization, and (2) identify the class of the object inside the box.</p>
<p>In the case of YOLOv4, it uses the same &quot;Head&quot; with that of YOLOv3.</p>
<p>To summarize, YOLOv4 has three main parts:</p>
<ol>
<li>Backbone --&gt; CSPDarknet53</li>
<li>Neck (Connects the backbone with the head) --&gt; SPP, PAN</li>
<li>Head --&gt; YOLOv3's Head</li>
</ol>
<p>References:</p>
<ul>
<li>Section 1.A. in <a href="https://ieeexplore.ieee.org/document/9214094" rel="noreferrer">https://ieeexplore.ieee.org/document/9214094</a></li>
<li>Page 5 of <a href="http://arxiv.org/abs/2004.10934" rel="noreferrer">http://arxiv.org/abs/2004.10934</a></li>
</ul>
Unable to understand YOLOv4 architecture
<p>I was going through <a href="https://arxiv.org/abs/2004.10934?" rel="nofollow noreferrer">yolov4</a> paper where the authors have mentioned Backbone(CSP DARKNET-53), Neck (SPP followed by PANet) &amp; than Head(YOLOv3). Hence is the architecture something like this:</p>
<p>CSP Darknet-53--&gt;SPP--&gt;PANet--&gt;YOLOv3(106 layers of YOLOv3).</p>
<p>Does this mean YOLOv4 incorporates entire YOLOv3?</p>