Search Results for author: Ningzhong Liu

Found 10 papers, 10 papers with code

SIDE: Self-supervised Intermediate Domain Exploration for Source-free Domain Adaptation

1 code implementation13 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.

Self-Supervised Learning Source-Free Domain Adaptation

Degradation-Aware Self-Attention Based Transformer for Blind Image Super-Resolution

1 code implementation6 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.

Blind Super-Resolution Contrastive Learning +2

FGFusion: Fine-Grained Lidar-Camera Fusion for 3D Object Detection

1 code implementation21 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.

3D Object Detection Autonomous Driving +1

A Task-aware Dual Similarity Network for Fine-grained Few-shot Learning

1 code implementation22 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.

Few-Shot Learning

Polycentric Clustering and Structural Regularization for Source-free Unsupervised Domain Adaptation

1 code implementation14 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.

Clustering Source-Free Domain Adaptation +1

Attention Guided Network for Salient Object Detection in Optical Remote Sensing Images

1 code implementation5 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.

object-detection Object Detection +2

A lightweight multi-scale context network for salient object detection in optical remote sensing images

1 code implementation18 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.

object-detection Object Detection +1

Robust Ensembling Network for Unsupervised Domain Adaptation

1 code implementation21 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.

Unsupervised Domain Adaptation

MPI: Multi-receptive and Parallel Integration for Salient Object Detection

1 code implementation8 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.

Object object-detection +2

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