https://hackerpaper.kaipfister.de/p/1703.03872/Collected HN comments and submissions linking this paper.enMon, 02 Nov 2026 11:16:22 GMThttps://news.ycombinator.com/item?id=22503448urn:hackerpapers:mention:1703.03872:22503448Fri, 06 Mar 2020 13:44:35 GMT<p>Depending on the type of image, a simple solution could be using OpenCV and some clever heuristics. For a deep learning approach, I would start by looking into literature on semantic segmentation. Here is a blog post I just found which gives an intro: [1] With state-of-the-art models (e.g. DeepLabV3) and a good dataset of foreground/background segmentations, the results could be of useful quality already. The next step would be to look into literature on image matting (e.g. deep image matting [2]) which instead of trying to classify each pixel as foreground/background, regresses the…</p><p><a href="https://hackerpaper.kaipfister.de/p/1703.03872/">Paper and discussion history</a>. A mention is not an endorsement.</p>cs.CVhttps://news.ycombinator.com/item?id=13937931urn:hackerpapers:submission:1703.03872:13937931Thu, 23 Mar 2017 07:27:18 GMT<p>Deep Image Matting</p><p></p><p>3 points; 0 discussion replies on HN. <a href="https://hackerpaper.kaipfister.de/p/1703.03872/">Paper and source history</a>. A submission is not an endorsement.</p>cs.CV