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Papers/Estimating Image Depth in the Comics Domain

Estimating Image Depth in the Comics Domain

Deblina Bhattacharjee, Martin Everaert, Mathieu Salzmann, Sabine Süsstrunk

2021-10-07Unsupervised Image-To-Image TranslationDepth PredictionTranslationDepth EstimationImage-to-Image Translation
PaperPDFCode(official)

Abstract

Estimating the depth of comics images is challenging as such images a) are monocular; b) lack ground-truth depth annotations; c) differ across different artistic styles; d) are sparse and noisy. We thus, use an off-the-shelf unsupervised image to image translation method to translate the comics images to natural ones and then use an attention-guided monocular depth estimator to predict their depth. This lets us leverage the depth annotations of existing natural images to train the depth estimator. Furthermore, our model learns to distinguish between text and images in the comics panels to reduce text-based artefacts in the depth estimates. Our method consistently outperforms the existing state-ofthe-art approaches across all metrics on both the DCM and eBDtheque images. Finally, we introduce a dataset to evaluate depth prediction on comics. Our project website can be accessed at https://github.com/IVRL/ComicsDepth.

Results

TaskDatasetMetricValueModel
Depth EstimationDCMAbs Rel0.251Bhattacharjee et al.
Depth EstimationDCMRMSE0.971Bhattacharjee et al.
Depth EstimationDCMRMSE log0.305Bhattacharjee et al.
Depth EstimationDCMSq Rel0.318Bhattacharjee et al.
Depth EstimationeBDthequeAbs Rel0.376Bhattacharjee et al.
Depth EstimationeBDthequeRMSE1.364Bhattacharjee et al.
Depth EstimationeBDthequeRMSE log0.553Bhattacharjee et al.
Depth EstimationeBDthequeSq Rel0.448Bhattacharjee et al.
3DDCMAbs Rel0.251Bhattacharjee et al.
3DDCMRMSE0.971Bhattacharjee et al.
3DDCMRMSE log0.305Bhattacharjee et al.
3DDCMSq Rel0.318Bhattacharjee et al.
3DeBDthequeAbs Rel0.376Bhattacharjee et al.
3DeBDthequeRMSE1.364Bhattacharjee et al.
3DeBDthequeRMSE log0.553Bhattacharjee et al.
3DeBDthequeSq Rel0.448Bhattacharjee et al.

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