Weakly Supervised Object Detection Using Complementary Learning and Instance Clustering

Weakly Supervised Object Detection Using Complementary Learning and Instance Clustering

Supervised object detection schemes use fully annotated training data, which is fairly expensive to constitute. Whereas, weakly supervised object detection (WSOD) uses only image-level annotations for training which are much simpler to acquire. WSOD is a challenging task since it aims to learn objec...

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Bibliographic Details
Main Authors: Mehwish Awan, Jitae Shin
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Weakly supervised object detection
complementary learning
discriminative features
instance clustering
deep learning
Online Access:https://ieeexplore.ieee.org/document/9107134/

Internet

https://ieeexplore.ieee.org/document/9107134/

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