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README.md

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We conduct several experiments of the state-of-the-art object detectors and the proposed CLCNet method on the proposed dataset, to demonstrate the effectiveness of CLCNet, Table 2 and Fig. 4.



<div align=center><img src="Images/Experiment-results.png" width="800" height="400" /></div>

<div align=center><img src="Images/Experiment-results.png" width="800" height="350" /></div>

Table 2: Comparison results of the algorithms on the proposed dataset. Detection results of all comparison methods on the

proposed dataset. The mark lc on the upper right corner indicates that its value is computed by the proposed metrics



<div align=center><img src="Images/show-results.jpg" width="800" height="400" /></div>

<div align=center><img src="Images/show-results.jpg" width="800" height="350" /></div>

Figure 4: Qualitative results of the proposed CLCNet method on the Locount dataset.