Search Results for author: Pau Gargallo

Found 2 papers, 0 papers with code

Mapillary Planet-Scale Depth Dataset

no code implementations ECCV 2020 Manuel López Antequera, Pau Gargallo, Markus Hofinger, Samuel Rota Bulò, Yubin Kuang, Peter Kontschieder

Learning-based methods produce remarkable results on single image depth tasks when trained on well-established benchmarks, however, there is a large gap from these benchmarks to real-world performance that is usually obscured by the common practice of fine-tuning on the target dataset.

CrowdDriven: A New Challenging Dataset for Outdoor Visual Localization

no code implementations ICCV 2021 Ara Jafarzadeh, Manuel Lopez Antequera, Pau Gargallo, Yubin Kuang, Carl Toft, Fredrik Kahl, Torsten Sattler

Visual localization is the problem of estimating the position and orientation from which a given image (or a sequence of images) is taken in a known scene.

Self-Driving Cars Visual Localization

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