2 citations · 6 across the 10 of their papers we have counts for
10 papers
SIDE: Self-supervised Intermediate Domain Exploration for Source-free Domain Adaptation
Jiamei Liu, Han Sun, Yizhen Jia +3
Domain adaptation aims to alleviate the domain shift when transferring the knowledge learned from the source domain to the target domain. Due to privacy issues, source-free domain…
Degradation-Aware Self-Attention Based Transformer for Blind Image Super-Resolution
Qingguo Liu, Pan Gao, Kang Han +2
Compared to CNN-based methods, Transformer-based methods achieve impressive image restoration outcomes due to their abilities to model remote dependencies. However, how to apply Tr…
FGFusion: Fine-Grained Lidar-Camera Fusion for 3D Object Detection
Zixuan Yin, Han Sun, Ningzhong Liu +2
Lidars and cameras are critical sensors that provide complementary information for 3D detection in autonomous driving. While most prevalent methods progressively downscale the 3D p…
A Task-aware Dual Similarity Network for Fine-grained Few-shot Learning
Yan Qi, Han Sun, Ningzhong Liu +1
The goal of fine-grained few-shot learning is to recognize sub-categories under the same super-category by learning few labeled samples. Most of the recent approaches adopt a singl…
Polycentric Clustering and Structural Regularization for Source-free Unsupervised Domain Adaptation
Xinyu Guan, Han Sun, Ningzhong Liu +1
Source-Free Domain Adaptation (SFDA) aims to solve the domain adaptation problem by transferring the knowledge learned from a pre-trained source model to an unseen target domain. M…
Attention Guided Network for Salient Object Detection in Optical Remote Sensing Images
Yuhan Lin, Han Sun, Ningzhong Liu +3
Due to the extreme complexity of scale and shape as well as the uncertainty of the predicted location, salient object detection in optical remote sensing images (RSI-SOD) is a very…
A lightweight multi-scale context network for salient object detection in optical remote sensing images
Yuhan Lin, Han Sun, Ningzhong Liu +3
Due to the more dramatic multi-scale variations and more complicated foregrounds and backgrounds in optical remote sensing images (RSIs), the salient object detection (SOD) for opt…
Robust Ensembling Network for Unsupervised Domain Adaptation
Han Sun, Lei Lin, Ningzhong Liu +1
Recently, in order to address the unsupervised domain adaptation (UDA) problem, extensive studies have been proposed to achieve transferrable models. Among them, the most prevalent…
Multi-scale Edge-based U-shape Network for Salient Object Detection
Han Sun, Yetong Bian, Ningzhong Liu +1
Deep-learning based salient object detection methods achieve great improvements. However, there are still problems existing in the predictions, such as blurry boundary and inaccura…
MPI: Multi-receptive and Parallel Integration for Salient Object Detection
Han Sun, Jun Cen, Ningzhong Liu +2
The semantic representation of deep features is essential for image context understanding, and effective fusion of features with different semantic representations can significantl…