Motion Basis Learning for Unsupervised Deep Homography Estimation with Subspace Projection

03/29/2021
by   Nianjin Ye, et al.
4

In this paper, we introduce a new framework for unsupervised deep homography estimation. Our contributions are 3 folds. First, unlike previous methods that regress 4 offsets for a homography, we propose a homography flow representation, which can be estimated by a weighted sum of 8 pre-defined homography flow bases. Second, considering a homography contains 8 Degree-of-Freedoms (DOFs) that is much less than the rank of the network features, we propose a Low Rank Representation (LRR) block that reduces the feature rank, so that features corresponding to the dominant motions are retained while others are rejected. Last, we propose a Feature Identity Loss (FIL) to enforce the learned image feature warp-equivariant, meaning that the result should be identical if the order of warp operation and feature extraction is swapped. With this constraint, the unsupervised optimization is achieved more effectively and more stable features are learned. Extensive experiments are conducted to demonstrate the effectiveness of all the newly proposed components, and results show our approach outperforms the state-of-the-art on the homography benchmark datasets both qualitatively and quantitatively.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 2

page 3

page 4

page 6

page 7

04/08/2019

Unsupervised Deep Epipolar Flow for Stationary or Dynamic Scenes

Unsupervised deep learning for optical flow computation has achieved pro...
01/24/2021

Low-rank signal subspace: parameterization, projection and signal estimation

The paper contains several theoretical results related to the weighted n...
12/13/2019

Multilayer Collaborative Low-Rank Coding Network for Robust Deep Subspace Discovery

For subspace recovery, most existing low-rank representation (LRR) model...
06/21/2021

Low-rank Dictionary Learning for Unsupervised Feature Selection

There exist many high-dimensional data in real-world applications such a...
05/07/2019

Locality and Structure Regularized Low Rank Representation for Hyperspectral Image Classification

Hyperspectral image (HSI) classification, which aims to assign an accura...
08/04/2019

Unsupervised Learning of Depth and Deep Representation for Visual Odometry from Monocular Videos in a Metric Space

For ego-motion estimation, the feature representation of the scenes is c...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.