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):
The workshop will be held on Sunday morning, June 16, 2019.
Please contact us on email@example.com.
The workshop features a challenge with multiple datasets and tasks.
More information TBA.
Please refer to the Call for Papers.
The prizes for the workshop challenge are sponsored by NVIDIA and Scape. Waiting on confirmation from other partners. Details TBA.