A Robust Context-Aware Proposal Refinement Method for Weakly Supervised Object Detection

A Robust Context-Aware Proposal Refinement Method for Weakly Supervised Object Detection

Supervised object detection models require fully annotated data for training the network. However, labeling large datasets is a very time-consuming task, therefore, weakly supervised object detection (WSOD) is a substitute approach to fully supervised learning for the object detection task. Many met...

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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
proposal refinement
class activation maps
reinforcement learning
Online Access:https://ieeexplore.ieee.org/document/9247225/

Internet

https://ieeexplore.ieee.org/document/9247225/

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