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  "author": "Yongtuo Liu",
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  "author": "Yongtuo Liu",
            
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  "extra_authors": [
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  "extra_authors": [
            
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    {
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    {
            
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      "extra_author": "Dan Xu",
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      "extra_author": "Dan Xu",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    {
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      "extra_author": "Sucheng Ren",
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      "extra_author": "Sucheng Ren",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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      "extra_author": "Hanjie Wu",
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      "extra_author": "Hanjie Wu",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "Hongmin Cai",
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      "extra_author": "Hongmin Cai",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "Shengfeng He",
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      "extra_author": "Shengfeng He",
            
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      "orcid": ""
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      "orcid": ""
            
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rained-domain-adaptive-crowd-counting-via-point-derived-segmentation",
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rained-domain-adaptive-crowd-counting-via-point-derived-segmentation",
            
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  "notes": "Crowd counting has drawn increasing attention because of 
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  "notes": "Crowd counting has drawn increasing attention because of 
            
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its fundamental role in social management. Six datasets are used in 
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its fundamental role in social management. Six datasets are used in 
            
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our experiments, i.e., GCC, ShanghaiTech PartA, ShanghaiTech PartB, 
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our experiments, i.e., GCC, ShanghaiTech PartA, ShanghaiTech PartB, 
            
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JHU-CROWD, MALL, and UCSD.",
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JHU-CROWD, MALL, and UCSD.",
            
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  "title": "Fine-grained Domain Adaptive Crowd Counting via 
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Point-derived Segmentation",
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Point-derived Segmentation",
            
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