We have located links that may give you full text access.
MICPL: Motion-Inspired Cross-Pattern Learning for Small-Object Detection in Satellite Videos.
For small-object detection, vision patterns can only provide limited support to feature learning. Most prior schemes mainly depend on a single vision pattern to learn object features, seldom considering more latent motion patterns. In the real world, humans often efficiently perceive small objects through multipattern signals. Inspired by this observation, this article attempts to address small-object detection from a new prospective of latent pattern learning. To fulfill this purpose, it regards a real-world moving object as the spatiotemporal sequences of a static object to capture latent motion patterns. In view of this, we propose a motion-inspired cross-pattern learning (MICPL) scheme to capture the motion patterns for moving small-object scenarios. This scheme mainly consists of two crucial parts: motion pattern mining (MPM) and motion-vision adaption. The former is designed to effectively mine the motion pattern from time-dependent representation space. The latter is devised to correlate between motion patterns and vision semantics. In the meanwhile, we explore their cross-pattern interactions to guide MICPL to capture motion patterns effectively. Comparison experiments verify that, cooperated by motion pattern, even a simple detector could often refresh state-of-the-art (SOTA) results on moving small-object detection. Moreover, the experiments on two small-object-related tasks further prove the adaptivity and advantages of our cross-pattern feature learning scheme. Our source codes are available at https://github.com/ UESTC-nnLab/MICPL.
Full text links
Related Resources
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app
All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.
By using this service, you agree to our terms of use and privacy policy.
Your Privacy Choices
You can now claim free CME credits for this literature searchClaim now
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app