Search Results for author: Baosheng Yu

Found 33 papers, 17 papers with code

Knowledge-Aware Federated Active Learning with Non-IID Data

1 code implementation24 Nov 2022 Yu-Tong Cao, Jingya Wang, Ye Shi, Baosheng Yu, DaCheng Tao

In this paper, we propose a federated active learning paradigm to efficiently learn a global model with limited annotation budget while protecting data privacy in a decentralized learning way.

Active Learning Federated Learning

Responsible Active Learning via Human-in-the-loop Peer Study

no code implementations24 Nov 2022 Yu-Tong Cao, Jingya Wang, Baosheng Yu, DaCheng Tao

To further enhance the active learner via large-scale unlabelled data, we introduce multiple peer students into the active learner which is trained by a novel learning paradigm, including the In-Class Peer Study on labelled data and the Out-of-Class Peer Study on unlabelled data.

Active Learning

Domain-Specific Risk Minimization for Out-of-Distribution Generalization

no code implementations18 Aug 2022 Yi-Fan Zhang, Jindong Wang, Jian Liang, Zhang Zhang, Baosheng Yu, Liang Wang, DaCheng Tao, Xing Xie

Our bound motivates two strategies to reduce the gap: the first one is ensembling multiple classifiers to enrich the hypothesis space, then we propose effective gap estimation methods for guiding the selection of a better hypothesis for the target.

Domain Generalization Out-of-Distribution Generalization

Improving Fine-Grained Visual Recognition in Low Data Regimes via Self-Boosting Attention Mechanism

1 code implementation1 Aug 2022 Yangyang Shu, Baosheng Yu, HaiMing Xu, Lingqiao Liu

In low data regimes, a network often struggles to choose the correct regions for recognition and tends to overfit spurious correlated patterns from the training data.

Fine-Grained Visual Recognition

MeshMAE: Masked Autoencoders for 3D Mesh Data Analysis

no code implementations20 Jul 2022 Yaqian Liang, Shanshan Zhao, Baosheng Yu, Jing Zhang, Fazhi He

We first randomly mask some patches of the mesh and feed the corrupted mesh into Mesh Transformers.

Deep Dictionary Learning with An Intra-class Constraint

no code implementations14 Jul 2022 Xia Yuan, Jianping Gou, Baosheng Yu, Jiali Yu, Zhang Yi

Specifically, we design the intra-class compactness constraint on the intermediate representation at different levels to encourage the intra-class representations to be closer to each other, and eventually the learned representation becomes more discriminative.~Unlike the traditional DDL methods, during the classification stage, our DDLIC performs a layer-wise greedy optimization in a similar way to the training stage.

Dictionary Learning Representation Learning

GFNet: Geometric Flow Network for 3D Point Cloud Semantic Segmentation

1 code implementation6 Jul 2022 Haibo Qiu, Baosheng Yu, DaCheng Tao

However, recent projection-based methods for point cloud semantic segmentation usually utilize a vanilla late fusion strategy for the predictions of different views, failing to explore the complementary information from a geometric perspective during the representation learning.

3D Semantic Segmentation LIDAR Semantic Segmentation +1

BatchFormerV2: Exploring Sample Relationships for Dense Representation Learning

1 code implementation4 Apr 2022 Zhi Hou, Baosheng Yu, Chaoyue Wang, Yibing Zhan, DaCheng Tao

Specifically, when applying the proposed module, it employs a two-stream pipeline during training, i. e., either with or without a BatchFormerV2 module, where the batchformer stream can be removed for testing.

Image Classification object-detection +3

Exploring High-Order Structure for Robust Graph Structure Learning

no code implementations22 Mar 2022 Guangqian Yang, Yibing Zhan, Jinlong Li, Baosheng Yu, Liu Liu, Fengxiang He

In this paper, we analyze the adversarial attack on graphs from the perspective of feature smoothness which further contributes to an efficient new adversarial defensive algorithm for GNNs.

Adversarial Attack Graph structure learning

Learning Affinity from Attention: End-to-End Weakly-Supervised Semantic Segmentation with Transformers

1 code implementation CVPR 2022 Lixiang Ru, Yibing Zhan, Baosheng Yu, Bo Du

Motivated by the inherent consistency between the self-attention in Transformers and the semantic affinity, we propose an Affinity from Attention (AFA) module to learn semantic affinity from the multi-head self-attention (MHSA) in Transformers.

Weakly supervised Semantic Segmentation Weakly-Supervised Semantic Segmentation

BatchFormer: Learning to Explore Sample Relationships for Robust Representation Learning

1 code implementation CVPR 2022 Zhi Hou, Baosheng Yu, DaCheng Tao

We perform extensive experiments on over ten datasets and the proposed method achieves significant improvements on different data scarcity applications without any bells and whistles, including the tasks of long-tailed recognition, compositional zero-shot learning, domain generalization, and contrastive learning.

Compositional Zero-Shot Learning Contrastive Learning +4

Hyper-relationship Learning Network for Scene Graph Generation

no code implementations15 Feb 2022 Yibing Zhan, Zhi Chen, Jun Yu, Baosheng Yu, DaCheng Tao, Yong Luo

As a result, HLN significantly improves the performance of scene graph generation by integrating and reasoning from object interactions, relationship interactions, and transitive inference of hyper-relationships.

Graph Attention Graph Generation +1

Resistance Training using Prior Bias: toward Unbiased Scene Graph Generation

1 code implementation18 Jan 2022 Chao Chen, Yibing Zhan, Baosheng Yu, Liu Liu, Yong Luo, Bo Du

To address this problem, we propose Resistance Training using Prior Bias (RTPB) for the scene graph generation.

Graph Generation Unbiased Scene Graph Generation

SkipNode: On Alleviating Performance Degradation for Deep Graph Convolutional Networks

no code implementations22 Dec 2021 Weigang Lu, Yibing Zhan, Binbin Lin, Ziyu Guan, Liu Liu, Baosheng Yu, Wei Zhao, Yaming Yang, DaCheng Tao

In this paper, we conduct theoretical and experimental analysis to explore the fundamental causes of performance degradation in deep GCNs: over-smoothing and gradient vanishing have a mutually reinforcing effect that causes the performance to deteriorate more quickly in deep GCNs.

Link Prediction Node Classification

Contrastive Graph Poisson Networks: Semi-Supervised Learning with Extremely Limited Labels

no code implementations NeurIPS 2021 Sheng Wan, Yibing Zhan, Liu Liu, Baosheng Yu, Shirui Pan, Chen Gong

Essentially, our CGPN can enhance the learning performance of GNNs under extremely limited labels by contrastively propagating the limited labels to the entire graph.

Graph Attention Node Classification +1

SynFace: Face Recognition with Synthetic Data

1 code implementation ICCV 2021 Haibo Qiu, Baosheng Yu, Dihong Gong, Zhifeng Li, Wei Liu, DaCheng Tao

We then analyze the underlying causes behind the performance gap, e. g., the poor intra-class variations and the domain gap between synthetic and real face images.

Face Generation Face Recognition

TGRNet: A Table Graph Reconstruction Network for Table Structure Recognition

1 code implementation ICCV 2021 Wenyuan Xue, Baosheng Yu, Wen Wang, DaCheng Tao, Qingyong Li

A table arranging data in rows and columns is a very effective data structure, which has been widely used in business and scientific research.

Graph Reconstruction Table Recognition

Learning Progressive Point Embeddings for 3D Point Cloud Generation

no code implementations CVPR 2021 Cheng Wen, Baosheng Yu, DaCheng Tao

The proposed dual-generators framework thus is able to progressively learn effective point embeddings for accurate point cloud generation.

Autonomous Driving Object Reconstruction +2

Affordance Transfer Learning for Human-Object Interaction Detection

2 code implementations CVPR 2021 Zhi Hou, Baosheng Yu, Yu Qiao, Xiaojiang Peng, DaCheng Tao

The proposed method can thus be used to 1) improve the performance of HOI detection, especially for the HOIs with unseen objects; and 2) infer the affordances of novel objects.

Affordance Detection Affordance Recognition +3

Detecting Human-Object Interaction via Fabricated Compositional Learning

1 code implementation CVPR 2021 Zhi Hou, Baosheng Yu, Yu Qiao, Xiaojiang Peng, DaCheng Tao

With the proposed object fabricator, we are able to generate large-scale HOI samples for rare and unseen categories to alleviate the open long-tailed issues in HOI detection.

Affordance Recognition Scene Understanding

Collaborative Teacher-Student Learning via Multiple Knowledge Transfer

no code implementations21 Jan 2021 Liyuan Sun, Jianping Gou, Baosheng Yu, Lan Du, DaCheng Tao

However, most of the existing knowledge distillation methods consider only one type of knowledge learned from either instance features or instance relations via a specific distillation strategy in teacher-student learning.

Knowledge Distillation Model Compression +2

Not All Operations Contribute Equally: Hierarchical Operation-Adaptive Predictor for Neural Architecture Search

no code implementations ICCV 2021 Ziye Chen, Yibing Zhan, Baosheng Yu, Mingming Gong, Bo Du

Despite their efficiency, current graph-based predictors treat all operations equally, resulting in biased topological knowledge of cell architectures.

Neural Architecture Search

Heatmap Regression via Randomized Rounding

2 code implementations1 Sep 2020 Baosheng Yu, DaCheng Tao

Previous methods to overcome the sub-pixel localization problem usually rely on high-resolution heatmaps.

Face Alignment Pose Estimation +2

Knowledge Distillation: A Survey

no code implementations9 Jun 2020 Jianping Gou, Baosheng Yu, Stephen John Maybank, DaCheng Tao

To this end, a variety of model compression and acceleration techniques have been developed.

Knowledge Distillation Model Compression +2

Unsupervised Domain Adaptation on Reading Comprehension

1 code implementation13 Nov 2019 Yu Cao, Meng Fang, Baosheng Yu, Joey Tianyi Zhou

On the other hand, it further reduces domain distribution discrepancy through conditional adversarial learning across domains.

Reading Comprehension Unsupervised Domain Adaptation

Building Effective Large-Scale Traffic State Prediction System: Traffic4cast Challenge Solution

1 code implementation11 Nov 2019 Yang Liu, Fanyou Wu, Baosheng Yu, Zhiyuan Liu, Jieping Ye

How to build an effective large-scale traffic state prediction system is a challenging but highly valuable problem.

Time Series Prediction

Deep Metric Learning With Tuplet Margin Loss

no code implementations ICCV 2019 Baosheng Yu, Dacheng Tao

Deep metric learning, in which the loss function plays a key role, has proven to be extremely useful in visual recognition tasks.

Metric Learning

Correcting the Triplet Selection Bias for Triplet Loss

1 code implementation ECCV 2018 Baosheng Yu, Tongliang Liu, Mingming Gong, Changxing Ding, DaCheng Tao

Considering that the number of triplets grows cubically with the size of training data, triplet mining is thus indispensable for efficiently training with triplet loss.

Face Recognition Fine-Grained Image Classification +5

Anchor Cascade for Efficient Face Detection

no code implementations9 May 2018 Baosheng Yu, DaCheng Tao

Face detection is essential to facial analysis tasks such as facial reenactment and face recognition.

Face Detection Face Recognition +1

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