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-andplay
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.
Publication Link: https://studios.disneyresearch.com/2026/05/31/guardians-of-the-hair-rescuing-soft-boundaries-in-depth-stereo-and-novel-views/
- Category
- CG VFX & Misc