Search Results for author: Binhui Xie

Found 16 papers, 14 papers with code

Few Clicks Suffice: Active Test-Time Adaptation for Semantic Segmentation

no code implementations4 Dec 2023 Longhui Yuan, Shuang Li, Zhuo He, Binhui Xie

Extensive experiments demonstrate that ATASeg bridges the performance gap between TTA methods and their supervised counterparts with only extremely few annotations, even one click for labeling surpasses known SOTA TTA methods by 2. 6% average mIoU on ACDC benchmark.

Active Learning Semantic Segmentation +1

Generalized Robust Test-Time Adaptation in Continuous Dynamic Scenarios

1 code implementation7 Oct 2023 Shuang Li, Longhui Yuan, Binhui Xie, Tao Yang

Test-time adaptation (TTA) adapts the pre-trained models to test distributions during the inference phase exclusively employing unlabeled test data streams, which holds great value for the deployment of models in real-world applications.

Test-time Adaptation

Robust Test-Time Adaptation in Dynamic Scenarios

1 code implementation CVPR 2023 Longhui Yuan, Binhui Xie, Shuang Li

Test-time adaptation (TTA) intends to adapt the pretrained model to test distributions with only unlabeled test data streams.

Autonomous Driving Test-time Adaptation

VBLC: Visibility Boosting and Logit-Constraint Learning for Domain Adaptive Semantic Segmentation under Adverse Conditions

1 code implementation22 Nov 2022 Mingjia Li, Binhui Xie, Shuang Li, Chi Harold Liu, Xinjing Cheng

However, previous methods often reckon on additional reference images of the same scenes taken from normal conditions, which are quite tough to collect in reality.

Domain Adaptation Semantic Segmentation

Joint Semantic Transfer Network for IoT Intrusion Detection

no code implementations28 Oct 2022 Jiashu Wu, Yang Wang, Binhui Xie, Shuang Li, Hao Dai, Kejiang Ye, Chengzhong Xu

The scenario semantic endows source NI and II domain with characteristics from each other to ease the knowledge transfer process via a confused domain discriminator and categorical distribution knowledge preservation.

Computational Efficiency Domain Adaptation +3

SePiCo: Semantic-Guided Pixel Contrast for Domain Adaptive Semantic Segmentation

1 code implementation19 Apr 2022 Binhui Xie, Shuang Li, Mingjia Li, Chi Harold Liu, Gao Huang, Guoren Wang

Domain adaptive semantic segmentation attempts to make satisfactory dense predictions on an unlabeled target domain by utilizing the supervised model trained on a labeled source domain.

Semantic Segmentation Synthetic-to-Real Translation

Active Learning for Domain Adaptation: An Energy-Based Approach

1 code implementation2 Dec 2021 Binhui Xie, Longhui Yuan, Shuang Li, Chi Harold Liu, Xinjing Cheng, Guoren Wang

Unsupervised domain adaptation has recently emerged as an effective paradigm for generalizing deep neural networks to new target domains.

Active Learning Transfer Learning +1

SPCL: A New Framework for Domain Adaptive Semantic Segmentation via Semantic Prototype-based Contrastive Learning

1 code implementation24 Nov 2021 Binhui Xie, Mingjia Li, Shuang Li

Although there is significant progress in supervised semantic segmentation, it remains challenging to deploy the segmentation models to unseen domains due to domain biases.

Contrastive Learning Domain Adaptation +4

Semantic Distribution-aware Contrastive Adaptation for Semantic Segmentation

1 code implementation11 May 2021 Shuang Li, Binhui Xie, Bin Zang, Chi Harold Liu, Xinjing Cheng, Ruigang Yang, Guoren Wang

Specifically, we first design a pixel-wise contrastive loss by considering the correspondences between semantic distributions and pixel-wise representations from both domains.

Self-Supervised Learning Semantic Segmentation

Generalized Domain Conditioned Adaptation Network

1 code implementation23 Mar 2021 Shuang Li, Binhui Xie, Qiuxia Lin, Chi Harold Liu, Gao Huang, Guoren Wang

Domain Adaptation (DA) attempts to transfer knowledge learned in the labeled source domain to the unlabeled but related target domain without requiring large amounts of target supervision.

Attribute Domain Adaptation

Bi-Classifier Determinacy Maximization for Unsupervised Domain Adaptation

1 code implementation13 Dec 2020 Shuang Li, Fangrui Lv, Binhui Xie, Chi Harold Liu, Jian Liang, Chen Qin

Motivated by the observation that target samples cannot always be separated distinctly by the decision boundary, here in the proposed BCDM, we design a novel classifier determinacy disparity (CDD) metric, which formulates classifier discrepancy as the class relevance of distinct target predictions and implicitly introduces constraint on the target feature discriminability.

Semantic Segmentation

Simultaneous Semantic Alignment Network for Heterogeneous Domain Adaptation

1 code implementation4 Aug 2020 Shuang Li, Binhui Xie, Jiashu Wu, Ying Zhao, Chi Harold Liu, Zhengming Ding

In this paper, we propose a Simultaneous Semantic Alignment Network (SSAN) to simultaneously exploit correlations among categories and align the centroids for each category across domains.

Domain Adaptation Pseudo Label

Domain Conditioned Adaptation Network

1 code implementation14 May 2020 Shuang Li, Chi Harold Liu, Qiuxia Lin, Binhui Xie, Zhengming Ding, Gao Huang, Jian Tang

Most existing deep DA models only focus on aligning feature representations of task-specific layers across domains while integrating a totally shared convolutional architecture for source and target.

Domain Adaptation

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