all AI news
Detecting Rotated Objects as Gaussian Distributions and Its 3-D Generalization. (arXiv:2209.10839v1 [cs.CV])
Sept. 23, 2022, 1:14 a.m. | Xue Yang, Gefan Zhang, Xiaojiang Yang, Yue Zhou, Wentao Wang, Jin Tang, Tao He, Junchi Yan
cs.CV updates on arXiv.org arxiv.org
Existing detection methods commonly use a parameterized bounding box (BBox)
to model and detect (horizontal) objects and an additional rotation angle
parameter is used for rotated objects. We argue that such a mechanism has
fundamental limitations in building an effective regression loss for rotation
detection, especially for high-precision detection with high IoU (e.g. 0.75).
Instead, we propose to model the rotated objects as Gaussian distributions. A
direct advantage is that our new regression loss regarding the distance between
two Gaussians …
More from arxiv.org / cs.CV updates on arXiv.org
Compact 3D Scene Representation via Self-Organizing Gaussian Grids
2 days, 10 hours ago |
arxiv.org
Fingerprint Matching with Localized Deep Representation
2 days, 10 hours ago |
arxiv.org
Jobs in AI, ML, Big Data
Founding AI Engineer, Agents
@ Occam AI | New York
AI Engineer Intern, Agents
@ Occam AI | US
AI Research Scientist
@ Vara | Berlin, Germany and Remote
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne