Per-pixel bounding-box regression + DBSCAN for handwritten word detection - visual walkthrough of WordDetectorNet [P]

Overview of WordDetectorNN architecture. Sharing a visual breakdown of WordDetectorNet, Harald Scheidl's handwritten-word detection model. I think the design choice at its core is unusual enough to be worth a closer look - and I haven't seen it written up in detail anywhere else. The mechanism: Instead of anchor-based detection + NMS, every pixel the network classifies as a "word pixel" also regresses 4 scalar distances (top/right/bottom/left) to the enclosing bounding box. Each word pixel therefore reconstructs one candidate box, producing thousands of overlapping candidates per word.