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GHOST framework enhances 3D reconstruction of transparent objects

By PulseAugur Editorial · [2 sources] ·

Researchers have developed GHOST, a novel framework designed to improve depth estimation and 3D reconstruction of transparent objects. This geometry-guided preprocessing method transforms transparent regions into opaque, structurally consistent representations. GHOST utilizes visual foundation models like TransDINO, TransDecomp, DAF-Net, and GeoSemTransNet to disentangle masks, physical properties, and surface normals, ultimately synthesizing an opaque RGB image that preserves the object's 3D structure. Experiments show GHOST significantly enhances the accuracy of existing depth estimation and reconstruction models when applied to transparent objects. AI

IMPACT Improves 3D reconstruction accuracy for transparent objects by restoring photometric cues.

RANK_REASON The cluster contains a research paper detailing a new method for computer vision.

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

GHOST framework enhances 3D reconstruction of transparent objects

COVERAGE [2]

  1. arXiv cs.CV TIER_1 English(EN) · Langxu Zhao, Zuan Gu, Tianhan Gao ·

    GHOST: Geometry-Guided Hallucination of Opaque Surface Textures

    arXiv:2607.11118v1 Announce Type: new Abstract: Transparent objects pose a fundamental challenge for depth estimation and 3D reconstruction due to their violation of Lambertian assumptions, leading to severe geometry degradation in downstream tasks. To address this, we propose a …

  2. arXiv cs.CV TIER_1 English(EN) · Tianhan Gao ·

    GHOST: Geometry-Guided Hallucination of Opaque Surface Textures

    Transparent objects pose a fundamental challenge for depth estimation and 3D reconstruction due to their violation of Lambertian assumptions, leading to severe geometry degradation in downstream tasks. To address this, we propose a novel geometry-guided preprocessing framework \t…

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