EBCDet: Energy-Based Curriculum for Robust Domain Adaptive Object Detection
This paper proposes a new method for addressing the problem of unsupervised domain adaptation for robust object detection. To this end, we propose an energy-based curriculum for progressively adapting a model, thereby mitigating the pseudo-label noise caused by domain shifts. Throughout the adaptati...
Main Authors: | Amin Banitalebi-Dehkordi, Abdollah Amirkhani, Alireza Mohammadinasab |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2023-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10192408/ |
Similar Items
-
Cross-Domain Object Detection by Dual Adaptive Branch
by: Xinyi Liu, et al.
Published: (2023-01-01) -
An Object Detection Method Based on Feature Uncertainty Domain Adaptation for Autonomous Driving
by: Yuan Zhu, et al.
Published: (2023-05-01) -
Adversarially Trained Object Detector for Unsupervised Domain Adaptation
by: Kazuma Fujii, et al.
Published: (2022-01-01) -
FedDAD: Federated Domain Adaptation for Object Detection
by: Peggy Joy Lu, et al.
Published: (2023-01-01) -
Spatial Alignment for Unsupervised Domain Adaptive Single-Stage Object Detection
by: Hong Liang, et al.
Published: (2022-04-01)