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20152022
most citeddocExtractor: An off-the-shelf historical document element extraction

34 citations · 93 across the 7 of their papers we have counts for

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21 papers · 1 filter

cs.CV2022

Focal Length and Object Pose Estimation via Render and Compare

Georgy Ponimatkin, Yann Labbé, Bryan Russell +2

We introduce FocalPose, a neural render-and-compare method for jointly estimating the camera-object 6D pose and camera focal length given a single RGB input image depicting a known…

cs.CV2021

Image Collation: Matching illustrations in manuscripts

Ryad Kaoua, Xi Shen, Alexandra Durr +3

Illustrations are an essential transmission instrument. For an historian, the first step in studying their evolution in a corpus of similar manuscripts is to identify which ones co…

cs.CV2021

Single-view robot pose and joint angle estimation via render & compare

Yann Labbé, Justin Carpentier, Mathieu Aubry +1

We introduce RoboPose, a method to estimate the joint angles and the 6D camera-to-robot pose of a known articulated robot from a single RGB image. This is an important problem to g…

cs.CV2021

Unsupervised Layered Image Decomposition into Object Prototypes

Tom Monnier, Elliot Vincent, Jean Ponce +1

We present an unsupervised learning framework for decomposing images into layers of automatically discovered object models. Contrary to recent approaches that model image layers wi…

cs.CV202034 cited

docExtractor: An off-the-shelf historical document element extraction

Tom Monnier, Mathieu Aubry

We present docExtractor, a generic approach for extracting visual elements such as text lines or illustrations from historical documents without requiring any real data annotation.…

cs.CV2020

Learning to Guide Local Feature Matches

François Darmon, Mathieu Aubry, Pascal Monasse

We tackle the problem of finding accurate and robust keypoint correspondences between images. We propose a learning-based approach to guide local feature matches via a learned appr…