1 code implementation • 25 Feb 2024 • Huan Ni, Yubin Zhao, Haiyan Guan, Cheng Jiang, Yongshi Jie, Xing Wang, Yiyang Shen
In this paper, we propose a Transformerbased weakly supervised method for cross-resolution land cover classification using outdated data.
no code implementations • 23 Jan 2023 • Yiyang Shen, Mingqiang Wei, Yongzhen Wang, Xueyang Fu, Jing Qin
Recent diffusion models have exhibited great potential in generative modeling tasks.
no code implementations • 17 Nov 2022 • Yiyang Shen, Rongwei Yu, Peng Wu, Haoran Xie, Lina Gong, Jing Qin, Mingqiang Wei
We propose ImLiDAR, a new 3OD paradigm to narrow the cross-sensor discrepancies by progressively fusing the multi-scale features of camera Images and LiDAR point clouds.
no code implementations • 28 Oct 2022 • Baian Chen, Lipeng Gu, Xin Zhuang, Yiyang Shen, Weiming Wang, Mingqiang Wei
We propose PSFormer, an effective point transformer model for 3D salient object detection.
1 code implementation • 28 Apr 2022 • Yiyang Shen, Yongzhen Wang, Mingqiang Wei, Honghua Chen, Haoran Xie, Gary Cheng, Fu Lee Wang
Rain is one of the most common weather which can completely degrade the image quality and interfere with the performance of many computer vision tasks, especially under heavy rain conditions.
1 code implementation • 6 Apr 2022 • Yiyang Shen, Mingqiang Wei, Sen Deng, Wenhan Yang, Yongzhen Wang, Xiao-Ping Zhang, Meng Wang, Jing Qin
To bridge the two domain gaps, we propose a semi-supervised detail-recovery image deraining network (Semi-DRDNet) with dual sample-augmented contrastive learning.
no code implementations • 21 May 2020 • Yiyang Shen, Yidan Feng, Sen Deng, Dong Liang, Jing Qin, Haoran Xie, Mingqiang Wei
We observe three intriguing phenomenons that, 1) rain is a mixture of raindrops, rain streaks and rainy haze; 2) the depth from the camera determines the degrees of object visibility, where objects nearby and faraway are visually blocked by rain streaks and rainy haze, respectively; and 3) raindrops on the glass randomly affect the object visibility of the whole image space.