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New study reveals evaluation flaws in image decomposition, proposes scene-level split

By PulseAugur Editorial · [2 sources] ·

A new paper identifies a significant flaw in how intrinsic image decomposition models are evaluated, specifically on the MPI Sintel dataset. Researchers found that splitting datasets by frames, rather than by scenes, leads to inflated performance metrics by up to 2.0 dB due to spatial similarity between training and testing frames. They propose using scene-level splits as the standard and demonstrate a new physics-informed decomposition method with source-separable uncertainty, which improves downstream tasks by filtering uncertain pixels. AI

IMPACT Highlights the need for more rigorous evaluation protocols in computer vision, potentially impacting how future decomposition models are benchmarked and developed.

RANK_REASON The cluster contains an academic paper detailing a new evaluation protocol and a novel method for intrinsic image decomposition.

Read on arXiv cs.CV →

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

New study reveals evaluation flaws in image decomposition, proposes scene-level split

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The cluster contains an academic paper detailing a new evaluation protocol and a novel method for intrinsic image decomposition.
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COVERAGE [2]

  1. arXiv cs.CV TIER_1 English(EN) · Jihwan Woo ·

    The frame-level leakage trap: rethinking evaluation protocols for intrinsic image decomposition, with source-separable uncertainty as a case study

    arXiv:2605.06359v1 Announce Type: cross Abstract: Evaluation protocols for learned intrinsic image decomposition on MPI Sintel have been inconsistent. Several prior works split the dataset by frames, which allows spatially similar frames of the same scene to appear in both train …

  2. arXiv cs.CV TIER_1 English(EN) · Jihwan Woo ·

    The frame-level leakage trap: rethinking evaluation protocols for intrinsic image decomposition, with source-separable uncertainty as a case study

    Evaluation protocols for learned intrinsic image decomposition on MPI Sintel have been inconsistent. Several prior works split the dataset by frames, which allows spatially similar frames of the same scene to appear in both train and test partitions. We quantify this leakage effe…

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