![[CVPR 2023] SOOD: Towards Semi-Supervised Oriented Object Detection](https://i.ytimg.com/vi/6Yn_Y4ghjhU/mqdefault.jpg)
Data is compiled from public records and verified media reports.
Last Updated: September 30, 2026
Disclaimer: Disclaimer: All information is compiled from publicly available data, media reports, and analysis. Actual details may vary.
Speaker: Ani Vanyan (YerevaNN) Topic: Authors: Seyed Mojtaba Marvasti-Zadeh; Nilanjan Ray; Nadir Erbilgin Description: Authors: Souradeep Chakraborty; Shujon Naha; Muhammet Bastan; Amit Kumar K. C.; Dimitris Samaras Description: In this paper, ... Authors: Weijia Zhang; Dongnan Liu; Chao Ma; Weidong Cai Description: Monocular 3D Description about our work: SOOD: Towards Gradient-based Sampling for Class Imbalanced Want to learn more about Generative AI + Machine Learning? Read the ebook → ibm.biz/BdGmGY Learn more about ... Authors: Na Zhao, Tat-Seng Chua, Gim Hee Lee Description: The performance of existing point cloud-based 3D In this video, we present our latest paper: “
Size: 4.05 MB · Format: PDF · Secure Download
Our platform aggregates the most comprehensive and up-to-date insights, ensuring you get relevant details about Semi Supervised Object Detection.
Interest in Semi Supervised Object Detection has surged recently as more people seek reliable resources, related media, and detailed analysis.
You can explore extensive galleries, video summaries, and related content directly on this page.
We regularly update our database with the latest information, media, and analysis related to Semi Supervised Object Detection.