Image Matching: Local Features & Beyond

CVPR 2019 Workshop

About

Traditional, keypoint-based formulations for image matching are still very competitive on tasks such as Structure from Motion (SfM), despite recent efforts on tackling pose estimation with dense networks. In practice, many state-of-the-art pipelines still rely on methods that stood the test of time, such as SIFT or RANSAC.

In this workshop, we aim to encourage novel strategies for image matching that deviate from and advance traditional formulations, with a focus on large-scale, wide-baseline matching for 3D reconstruction or pose estimation. This can be achieved by applying new technologies to sparse feature matching, or doing away with keypoints and descriptors entirely.

The workshop topics include (but are not limited to):

Organisers

Vassileios
Balntas
Scape Technologies
Vincent
Lepetit
University of Bordeaux
Johannes
Schönberger
Microsoft
Eduard
Trulls
Google
Kwang Moo
Yi
University of Victoria

The workshop will be held on Sunday morning, June 16, 2019.

Please contact us on imagematching@uvic.ca.

Invited Speakers

Torsten
Sattler
Chalmers University of Technology
Amir
Zamir
Stanford & Berkeley
Jiri
Matas
Czech Technical University

News

Important dates

(Deadlines are 11:59PM in Pacific Time.)

Challenge

The workshop features a challenge with multiple datasets and tasks.

Programme

More information TBA.

Paper Submission

Please refer to the Call for Papers.

Sponsorship

The prizes for the workshop challenge are sponsored by Google and Scape.

Google Scape