11 citations · 14 across the 4 of their papers we have counts for
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cs.CV2023
ViLTA: Enhancing Vision-Language Pre-training through Textual Augmentation
Weihan Wang, Zhen Yang, Bin Xu +2
Vision-language pre-training (VLP) methods are blossoming recently, and its crucial goal is to jointly learn visual and textual features via a transformer-based architecture, demon…
cs.CV2023★ 3 cited
CLIP: Contrastive Language-Image-Point Pretraining from Real-World Point Cloud Data
Yihan Zeng, Chenhan Jiang, Jiageng Mao +7
Contrastive Language-Image Pre-training, benefiting from large-scale unlabeled text-image pairs, has demonstrated great performance in open-world vision understanding tasks. Howeve…
cs.CV2017★ 11 cited
Learning a Dilated Residual Network for SAR Image Despeckling
Qiang Zhang, Qiangqiang Yuan, Jie Li +2
In this paper, to break the limit of the traditional linear models for synthetic aperture radar (SAR) image despeckling, we propose a novel deep learning approach by learning a non…