24 citations · 62 across the 13 of their papers we have counts for
Showing cs.CVShow all
3 papers · 1 filter
cs.CV2022★ 7 cited
Towards Robust Dataset Learning
Yihan Wu, Xinda Li, Florian Kerschbaum +2
Adversarial training has been actively studied in recent computer vision research to improve the robustness of models. However, due to the huge computational cost of generating adv…
cs.CV2022★ 2 cited
Decompose to Adapt: Cross-domain Object Detection via Feature Disentanglement
Dongnan Liu, Chaoyi Zhang, Yang Song +4
Recent advances in unsupervised domain adaptation (UDA) techniques have witnessed great success in cross-domain computer vision tasks, enhancing the generalization ability of data-…
cs.CV2021★ 8 cited
Data Augmentation for Object Detection via Differentiable Neural Rendering
Guanghan Ning, Guang Chen, Chaowei Tan +3
It is challenging to train a robust object detector under the supervised learning setting when the annotated data are scarce. Thus, previous approaches tackling this problem are in…