Unsupervised Domain Adaptive Object Detection using Forward-Backward Cyclic AdaptationWe present a novel approach to perform the unsupervised domain adaptation for object detection through forward-backward cyclic (FBC) training. Recent adversarial training based domain adaptation methods have shown their ...
DEEP DOMAIN ADAPTIVE OBJECT DETECTION: A SURVEY 摘要:基于深度学习的目标检测获得了很大的方法。这些方法基本上假定可以获得大规模的训练标签,训练和测试数据服从理想的分布。然而这两个假设在实际中通常不满足。深度域适配目标检测做为一种新的学习范式开始出现,来解决上述问题。这篇文章旨在对最先进的域适配目标检测...
Different from traditional approaches, we propose ConfMix, the first method that introduces a sample mixing strategy based on region-level detection confidence for adaptive object detector learning. We mix the local region of the target sample that corresponds to the most confident pseudo detections ...
首先,它们通常需要用于训练的源领域和目标领域的数据集,限制了它们的使用。此外,它们在局部不一致性方面存在问题,主要是因为由于缺乏目标领域注释,导致特征空间分布的内部分布未知。最后,不同领域数据集中的样本之间大量有用的信息被忽略,导致性能不佳。另一种方法利用自训练进行领域自适应检测[45, 24, 25]。其核心思...
Mega-cda: Memory guided attention for category-aware unsupervised domain adaptive object detection. In Proceedings of the IEEE/CVF Confer- ence on Computer Vision and Pattern Recognition, pages 4516–4526, 2021. 2, 3 [43] Yan Wang, Xiangyu Chen, Yurong You, Li Erran ...
Recent advances in deep learning significantly boost the performance of salient object detection (SOD) at the expense of labeling larger-scale per-pixel annotations. To relieve the burden of labor-intensive labeling, deep unsupervised SOD methods have been proposed to exploit noisy labels generated by...
Monocular 3D object detection (Mono3D) has achieved unprecedented success with the advent of deep learning techniques and emerging large-scale autonomous driving datasets. However, drastic performance degradation remains an unwell-studied challenge for practical cross-domain deployment as the lack of ...
To address the difficulty of collecting manually labeled training samples for object detection tasks, this paper proposes an unsupervised cross-domain object detection method that gradually adapts the model at pixel level and feature level. The existing
Official implementation of "Align and Distill: Unifying and Improving Domain Adaptive Object Detection" machine-learningcomputer-visionobject-detectiondomain-adaptationunsupervised-domain-adaptationdomain-adaptive-object-detection UpdatedAug 29, 2024 Python ...
We present a new domain adaptive self-training pipeline, named ST3D, for unsupervised domain adaptation on 3D object detection from point clouds. First, we pre-train the 3D detector on the source domain with our proposed random object scaling strategy for mitigating the negative effects of source...