5 citations · 7 across the 3 of their papers we have counts for
3 papers
cs.CV2022★ 2 cited
Out-of-Candidate Rectification for Weakly Supervised Semantic Segmentation
Zesen Cheng, Pengchong Qiao, Kehan Li +6
Weakly supervised semantic segmentation is typically inspired by class activation maps, which serve as pseudo masks with class-discriminative regions highlighted. Although tremendo…
cs.CV2022★ 5 cited
ACSeg: Adaptive Conceptualization for Unsupervised Semantic Segmentation
Kehan Li, Zhennan Wang, Zesen Cheng +6
Recently, self-supervised large-scale visual pre-training models have shown great promise in representing pixel-level semantic relationships, significantly promoting the developmen…
eess.SP2022
Time-Frequency Mask Aware Bi-directional LSTM: A Deep Learning Approach for Underwater Acoustic Signal Separation
Jie Chen, Chang Liu, Jiawu Xie +2
The underwater acoustic signals separation is a key technique for the underwater communications. The existing methods are mostly model-based, and could not accurately characterise…