Guardians of the Hair: Rescuing Soft Boundaries in Depth, Stereo, and Novel Views

• URL: http://arxiv.org/abs/2601.03362v1
• Date: Tue, 06 Jan 2026 19:02:34 GMT
• Title: Guardians of the Hair: Rescuing Soft Boundaries in Depth, Stereo, and Novel Views
• Authors: Xiang Zhang, Yang Zhang, Lukas Mehl, Markus Gross, Christopher Schroers,
• Abstract summary: This paper introduces HairGuard, a framework designed to recover fine-grained soft boundary details in 3D vision tasks.<n>Experiments demonstrate that HairGuard achieves state-of-the-art performance across monocular depth estimation, stereo image/video conversion, and novel view synthesis.
• Score: 20.270591069701677
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Soft boundaries, like thin hairs, are commonly observed in natural and computer-generated imagery, but they remain challenging for 3D vision due to the ambiguous mixing of foreground and background cues. This paper introduces Guardians of the Hair (HairGuard), a framework designed to recover fine-grained soft boundary details in 3D vision tasks. Specifically, we first propose a novel data curation pipeline that leverages image matting datasets for training and design a depth fixer network to automatically identify soft boundary regions. With a gated residual module, the depth fixer refines depth precisely around soft boundaries while maintaining global depth quality, allowing plug-and-play integration with state-of-the-art depth models. For view synthesis, we perform depth-based forward warping to retain high-fidelity textures, followed by a generative scene painter that fills disoccluded regions and eliminates redundant background artifacts within soft boundaries. Finally, a color fuser adaptively combines warped and inpainted results to produce novel views with consistent geometry and fine-grained details. Extensive experiments demonstrate that HairGuard achieves state-of-the-art performance across monocular depth estimation, stereo image/video conversion, and novel view synthesis, with significant improvements in soft boundary regions.

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