ProDyG: Progressive Dynamic Scene Reconstruction via Gaussian Splatting from Monocular Videos

• URL: http://arxiv.org/abs/2509.17864v1
• Date: Mon, 22 Sep 2025 14:58:11 GMT
• Title: ProDyG: Progressive Dynamic Scene Reconstruction via Gaussian Splatting from Monocular Videos
• Abstract summary: Existing SLAM methods typically merely remove the dynamic parts or require RGB-D input, while offline methods are not scalable to long video sequences.<n>We achieve online dynamic scene reconstruction by disentangling the static and dynamic parts within a SLAM system.<n>Our method yields novel view renderings competitive to offline methods and achieves on-par tracking with state-of-the-art dynamic SLAM methods.
• Score: 23.98157113623466
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: Achieving truly practical dynamic 3D reconstruction requires online operation, global pose and map consistency, detailed appearance modeling, and the flexibility to handle both RGB and RGB-D inputs. However, existing SLAM methods typically merely remove the dynamic parts or require RGB-D input, while offline methods are not scalable to long video sequences, and current transformer-based feedforward methods lack global consistency and appearance details. To this end, we achieve online dynamic scene reconstruction by disentangling the static and dynamic parts within a SLAM system. The poses are tracked robustly with a novel motion masking strategy, and dynamic parts are reconstructed leveraging a progressive adaptation of a Motion Scaffolds graph. Our method yields novel view renderings competitive to offline methods and achieves on-par tracking with state-of-the-art dynamic SLAM methods.

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