It predicts the visibility of each hand joint 👋<br>We hope researchers across HCI, robotics, hand-object interaction, and beyond will find hand visibility estimation useful in their own work!</p>\n<p>The code has been available on GitHub for a while, and I’m glad to see it already receiving stars⭐️ and interest from the community! 🙌<br>Please give it a try!</p>\n<p>📄 <a href=\"https://arxiv.org/abs/2608.11574\" rel=\"nofollow\">https://arxiv.org/abs/2608.11574</a><br>💻️ <a href=\"https://github.com/ryhara/hand_visibility_detector\" rel=\"nofollow\">https://github.com/ryhara/hand_visibility_detector</a></p>\n","updatedAt":"2026-08-13T06:33:59.311Z","author":{"_id":"639c144bf44c46d8af63b8f9","avatarUrl":"/avatars/de32f82f4befd43e3f9099e6ed6345a1.svg","fullname":"Ryosei Hara","name":"ryhara","type":"user","isPro":false,"isHf":false,"isHfAdmin":false,"isMod":false,"isUserFollowing":false}},"numEdits":0,"identifiedLanguage":{"language":"en","probability":0.9094869494438171},"editors":["ryhara"],"editorAvatarUrls":["/avatars/de32f82f4befd43e3f9099e6ed6345a1.svg"],"reactions":[],"isReport":false}}],"primaryEmailConfirmed":false,"paper":{"id":"2608.11574","authors":[{"_id":"6a7d1bfd0ac8bee77474ede2","user":{"_id":"639c144bf44c46d8af63b8f9","avatarUrl":"/avatars/de32f82f4befd43e3f9099e6ed6345a1.svg","isPro":false,"fullname":"Ryosei Hara","user":"ryhara","type":"user","name":"ryhara"},"name":"Ryosei Hara","status":"claimed_verified","statusLastChangedAt":"2026-08-13T08:45:04.997Z","hidden":false},{"_id":"6a7d1bfd0ac8bee77474ede3","name":"Masashi Hatano","hidden":false},{"_id":"6a7d1bfd0ac8bee77474ede4","name":"Rintaro Yanagi","hidden":false},{"_id":"6a7d1bfd0ac8bee77474ede5","name":"Atsushi Hashimoto","hidden":false},{"_id":"6a7d1bfd0ac8bee77474ede6","name":"Takuma Yagi","hidden":false},{"_id":"6a7d1bfd0ac8bee77474ede7","name":"Mariko Isogawa","hidden":false}],"publishedAt":"2026-08-12T00:00:00.000Z","submittedOnDailyAt":"2026-08-13T00:00:00.000Z","title":"Hand Visibility Detector: Per-Keypoint Visibility Estimation for Hands","submittedOnDailyBy":{"_id":"639c144bf44c46d8af63b8f9","avatarUrl":"/avatars/de32f82f4befd43e3f9099e6ed6345a1.svg","isPro":false,"fullname":"Ryosei Hara","user":"ryhara","type":"user","name":"ryhara"},"summary":"Hand Pose Estimation (HPE) is a fundamental technology for various applications such as AR/VR and robotics. In these applications, the visibility of each hand joint in the image is crucial for assessing the reliability of estimation results under occlusion. However, most existing HPE methods output joint positions without explicitly indicating their visibility. Although some methods account for occlusion or visibility, visibility estimation has mainly been used as an auxiliary signal for improving pose estimation. To our knowledge, per-joint hand visibility estimation has not been systematically studied as a standalone task. In this work, we propose Hand Visibility Detector, a model for estimating the visibility of individual hand joints, and present the first systematic investigation of visibility estimation as an independent task. We show that leveraging the prior knowledge of HPE models pretrained on large-scale data as a backbone yields high performance in this task. We further demonstrate the utility of Hand Visibility Detector on a downstream task of 3D hand pose annotation via multi-view triangulation of 2D keypoints, showing that visibility-weighted triangulation reduces reprojection error. Our method is released as a ready-to-use package, and the code and demo are available at https://github.com/ryhara/hand_visibility_detector .","upvotes":1,"discussionId":"6a7d1bfd0ac8bee77474ede8","githubRepo":"https://github.com/ryhara/hand_visibility_detector","githubRepoAddedBy":"user","ai_summary":"This work introduces a dedicated model for per-joint hand visibility estimation and demonstrates its benefit for multi-view 3D hand pose annotation.","ai_keywords":["Hand Pose Estimation","visibility estimation","Hand Visibility Detector","multi-view triangulation","visibility-weighted triangulation","reprojection error"],"ai_summary_model":"thinkingmachines/Inkling-Small","githubStars":30},"canReadDatabase":false,"canManagePapers":false,"canSubmit":false,"hasHfLevelAccess":false,"upvoted":false,"upvoters":[{"_id":"639c144bf44c46d8af63b8f9","avatarUrl":"/avatars/de32f82f4befd43e3f9099e6ed6345a1.svg","isPro":false,"fullname":"Ryosei Hara","user":"ryhara","type":"user"}],"acceptLanguages":["en"],"dailyPaperRank":0,"markdownContentUrl":"https://huggingface.co/buckets/huggingchat/papers-content/resolve/2608/2608.11574.md","query":{}}">

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