1 code implementation • 13 Oct 2023 • Jiamei Liu, Han Sun, Yizhen Jia, Jie Qin, Huiyu Zhou, Ningzhong Liu
Domain adaptation aims to alleviate the domain shift when transferring the knowledge learned from the source domain to the target domain.
1 code implementation • 6 Oct 2023 • Qingguo Liu, Pan Gao, Kang Han, Ningzhong Liu, Wei Xiang
In particular, we integrate both CNN and Transformer components into the SR network, where we first use the CNN modulated by the degradation information to extract local features, and then employ the degradation-aware Transformer to extract global semantic features.
1 code implementation • 21 Sep 2023 • Zixuan Yin, Han Sun, Ningzhong Liu, Huiyu Zhou, Jiaquan Shen
In this paper, we propose Fine-Grained Lidar-Camera Fusion (FGFusion) that make full use of multi-scale features of image and point cloud and fuse them in a fine-grained way.
1 code implementation • 22 Oct 2022 • Yan Qi, Han Sun, Ningzhong Liu, Huiyu Zhou
The goal of fine-grained few-shot learning is to recognize sub-categories under the same super-category by learning few labeled samples.
1 code implementation • 14 Oct 2022 • Xinyu Guan, Han Sun, Ningzhong Liu, Huiyu Zhou
In this paper, a novel framework named PCSR is proposed to tackle SFDA via a novel intra-class Polycentric Clustering and Structural Regularization strategy.
1 code implementation • 5 Jul 2022 • Yuhan Lin, Han Sun, Ningzhong Liu, Yetong Bian, Jun Cen, Huiyu Zhou
Specifically, the position enhancement stage consists of a semantic attention module and a contextual attention module to accurately describe the approximate location of salient objects.
1 code implementation • 18 May 2022 • Yuhan Lin, Han Sun, Ningzhong Liu, Yetong Bian, Jun Cen, Huiyu Zhou
Meanwhile, in order to accurately detect complete salient objects in complex backgrounds, we design an attention-based pyramid feature aggregation mechanism for gradually aggregating and refining the salient regions from the multi-scale context extraction module.
1 code implementation • 21 Aug 2021 • Han Sun, Lei Lin, Ningzhong Liu, Huiyu Zhou
In this paper, we propose a Robust Ensembling Network (REN) for UDA, which applies a robust time ensembling teacher network to learn global information for domain transfer.
1 code implementation • 21 Aug 2021 • Han Sun, Yetong Bian, Ningzhong Liu, Huiyu Zhou
Deep-learning based salient object detection methods achieve great improvements.
1 code implementation • 8 Aug 2021 • Han Sun, Jun Cen, Ningzhong Liu, Dong Liang, Huiyu Zhou
The semantic representation of deep features is essential for image context understanding, and effective fusion of features with different semantic representations can significantly improve the model's performance on salient object detection.