Search Results for author: Lei Qi

Found 16 papers, 5 papers with code

Inconsistency-aware Uncertainty Estimation for Semi-supervised Medical Image Segmentation

1 code implementation17 Oct 2021 Yinghuan Shi, Jian Zhang, Tong Ling, Jiwen Lu, Yefeng Zheng, Qian Yu, Lei Qi, Yang Gao

In semi-supervised medical image segmentation, most previous works draw on the common assumption that higher entropy means higher uncertainty.

Medical Image Segmentation

Better Pseudo-label: Joint Domain-aware Label and Dual-classifier for Semi-supervised Domain Generalization

no code implementations10 Oct 2021 Ruiqi Wang, Lei Qi, Yinghuan Shi, Yang Gao

With the goal of directly generalizing trained models to unseen target domains, domain generalization (DG), a newly proposed learning paradigm, has attracted considerable attention.

Domain Generalization

Crosslink-Net: Double-branch Encoder Segmentation Network via Fusing Vertical and Horizontal Convolutions

1 code implementation24 Jul 2021 Qian Yu, Lei Qi, Luping Zhou, Lei Wang, Yilong Yin, Yinghuan Shi, Wuzhang Wang, Yang Gao

Together, the above two schemes give rise to a novel double-branch encoder segmentation framework for medical image segmentation, namely Crosslink-Net.

Medical Image Segmentation

Learngene: From Open-World to Your Learning Task

no code implementations12 Jun 2021 Qiufeng Wang, Xin Geng, Shuxia Lin, Shiyu Xia, Lei Qi, Ning Xu

Although deep learning has made significant progress on fixed large-scale datasets, it typically encounters challenges regarding improperly detecting new/unseen classes in the open-world classification, over-parametrized, and overfitting small samples.

ST++: Make Self-training Work Better for Semi-supervised Semantic Segmentation

1 code implementation9 Jun 2021 Lihe Yang, Wei Zhuo, Lei Qi, Yinghuan Shi, Yang Gao

In this paper, we investigate if we could make the self-training -- a simple but popular framework -- work better for semi-supervised segmentation.

Semi-Supervised Semantic Segmentation

Feature-based Style Randomization for Domain Generalization

no code implementations6 Jun 2021 Yue Wang, Lei Qi, Yinghuan Shi, Yang Gao

As a recent noticeable topic, domain generalization (DG) aims to first learn a generic model on multiple source domains and then directly generalize to an arbitrary unseen target domain without any additional adaption.

Data Augmentation Domain Generalization

Mining Latent Classes for Few-shot Segmentation

1 code implementation ICCV 2021 Lihe Yang, Wei Zhuo, Lei Qi, Yinghuan Shi, Yang Gao

Our method aims to alleviate this problem and enhance the feature embedding on latent novel classes.

Rectification

Deep Symmetric Adaptation Network for Cross-modality Medical Image Segmentation

no code implementations18 Jan 2021 Xiaoting Han, Lei Qi, Qian Yu, Ziqi Zhou, Yefeng Zheng, Yinghuan Shi, Yang Gao

These typical methods usually utilize a translation network to transform images from the source domain to target domain or train the pixel-level classifier merely using translated source images and original target images.

Medical Image Segmentation Translation +1

Differentiable Meta-learning Model for Few-shot Semantic Segmentation

no code implementations23 Nov 2019 Pinzhuo Tian, Zhangkai Wu, Lei Qi, Lei Wang, Yinghuan Shi, Yang Gao

To address the annotation scarcity issue in some cases of semantic segmentation, there have been a few attempts to develop the segmentation model in the few-shot learning paradigm.

Few-Shot Semantic Segmentation Semantic Segmentation

Progressive Cross-camera Soft-label Learning for Semi-supervised Person Re-identification

no code implementations15 Aug 2019 Lei Qi, Lei Wang, Jing Huo, Yinghuan Shi, Yang Gao

In this paper, we focus on the semi-supervised person re-identification (Re-ID) case, which only has the intra-camera (within-camera) labels but not inter-camera (cross-camera) labels.

Semi-Supervised Person Re-Identification

GreyReID: A Two-stream Deep Framework with RGB-grey Information for Person Re-identification

no code implementations14 Aug 2019 Lei Qi, Lei Wang, Jing Huo, Yinghuan Shi, Yang Gao

Moreover, in the training process, we adopt the joint learning scheme to simultaneously train each branch by the independent loss function, which can enhance the generalization ability of each branch.

Person Re-Identification

Adversarial Camera Alignment Network for Unsupervised Cross-camera Person Re-identification

no code implementations2 Aug 2019 Lei Qi, Lei Wang, Jing Huo, Yinghuan Shi, Xin Geng, Yang Gao

To achieve the camera alignment, we develop a Multi-Camera Adversarial Learning (MCAL) to map images of different cameras into a shared subspace.

Person Re-Identification

A Novel Unsupervised Camera-aware Domain Adaptation Framework for Person Re-identification

no code implementations ICCV 2019 Lei Qi, Lei Wang, Jing Huo, Luping Zhou, Yinghuan Shi, Yang Gao

For the first issue, we highlight the presence of camera-level sub-domains as a unique characteristic of person Re-ID, and develop camera-aware domain adaptation to reduce the discrepancy not only between source and target domains but also across these sub-domains.

Person Re-Identification Representation Learning +1

MaskReID: A Mask Based Deep Ranking Neural Network for Person Re-identification

no code implementations11 Apr 2018 Lei Qi, Jing Huo, Lei Wang, Yinghuan Shi, Yang Gao

Lastly, considering person retrieval is a special image retrieval task, we propose a novel ranking loss to optimize the whole network.

Image Retrieval Person Re-Identification +1

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