Search Results for author: Yilong Yin

Found 39 papers, 16 papers with code

How Well Does GPT-4V(ision) Adapt to Distribution Shifts? A Preliminary Investigation

1 code implementation12 Dec 2023 Zhongyi Han, Guanglin Zhou, Rundong He, Jindong Wang, Tailin Wu, Yilong Yin, Salman Khan, Lina Yao, Tongliang Liu, Kun Zhang

We further investigate its adaptability to controlled data perturbations and examine the efficacy of in-context learning as a tool to enhance its adaptation.

Anomaly Detection Autonomous Driving +6

DiffAIL: Diffusion Adversarial Imitation Learning

1 code implementation11 Dec 2023 Bingzheng Wang, Guoqiang Wu, Teng Pang, Yan Zhang, Yilong Yin

To address this issue, we propose a method named diffusion adversarial imitation learning (DiffAIL), which introduces the diffusion model into the AIL framework.

Imitation Learning

Improving Generalization in Meta-Learning via Meta-Gradient Augmentation

1 code implementation14 Jun 2023 Ren Wang, Haoliang Sun, Qi Wei, Xiushan Nie, Yuling Ma, Yilong Yin

The key idea is to first break the rote memories by network pruning to address memorization overfitting in the inner loop, and then the gradients of pruned sub-networks naturally form the high-quality augmentation of the meta-gradient to alleviate learner overfitting in the outer loop.

Few-Shot Learning Memorization +1

Towards Understanding Generalization of Macro-AUC in Multi-label Learning

1 code implementation9 May 2023 Guoqiang Wu, Chongxuan Li, Yilong Yin

We theoretically identify a critical factor of the dataset affecting the generalization bounds: \emph{the label-wise class imbalance}.

Generalization Bounds Multi-Label Learning

MetaViewer: Towards A Unified Multi-View Representation

no code implementations CVPR 2023 Ren Wang, Haoliang Sun, Yuling Ma, Xiaoming Xi, Yilong Yin

To overcome them, we propose a novel bi-level-optimization-based multi-view learning framework, where the representation is learned in a uniform-to-specific manner.

MULTI-VIEW LEARNING Representation Learning

Fine-Grained Classification with Noisy Labels

no code implementations CVPR 2023 Qi Wei, Lei Feng, Haoliang Sun, Ren Wang, Chenhui Guo, Yilong Yin

To this end, we propose a novel framework called stochastic noise-tolerated supervised contrastive learning (SNSCL) that confronts label noise by encouraging distinguishable representation.

Classification Contrastive Learning +1

MHPL: Minimum Happy Points Learning for Active Source Free Domain Adaptation

no code implementations CVPR 2023 Fan Wang, Zhongyi Han, Zhiyan Zhang, Rundong He, Yilong Yin

Source free domain adaptation (SFDA) aims to transfer a trained source model to the unlabeled target domain without accessing the source data.

Active Learning Source-Free Domain Adaptation

Topological Structure Learning for Weakly-Supervised Out-of-Distribution Detection

no code implementations16 Sep 2022 Rundong He, Rongxue Li, Zhongyi Han, Yilong Yin

Based on limited ID labeled data and sufficient unlabeled data, we define a new setting called Weakly-Supervised Out-of-Distribution Detection (WSOOD).

Contrastive Learning Out-of-Distribution Detection +1

Self-Filtering: A Noise-Aware Sample Selection for Label Noise with Confidence Penalization

1 code implementation24 Aug 2022 Qi Wei, Haoliang Sun, Xiankai Lu, Yilong Yin

Sample selection is an effective strategy to mitigate the effect of label noise in robust learning.

Learning with noisy labels

DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement

3 code implementations12 Jun 2022 Yuhang Dong, Gongping Yang, Yilong Yin

Besides, a plug-and-play Spatial Attention Block (SAB) is proposed to enhance features along with the spatial location information.

 Ranked #1 on Heart rate estimation on VIPL-HR (using extra training data)

Heart rate estimation Photoplethysmography (PPG) heart rate estimation

Neural Network Compression via Effective Filter Analysis and Hierarchical Pruning

no code implementations7 Jun 2022 Ziqi Zhou, Li Lian, Yilong Yin, Ze Wang

Guided by that maximum rate, a novel and efficient hierarchical network pruning algorithm is developed to maximally condense the neuronal network structure without sacrificing network performance.

Network Pruning Neural Network Compression

Active Source Free Domain Adaptation

no code implementations22 May 2022 Fan Wang, Zhongyi Han, Zhiyan Zhang, Yilong Yin

We then propose minimum happy points learning (MHPL) to actively explore and exploit MH points.

Source-Free Domain Adaptation

Exploring Linear Feature Disentanglement For Neural Networks

no code implementations22 Mar 2022 Tiantian He, Zhibin Li, Yongshun Gong, Yazhou Yao, Xiushan Nie, Yilong Yin

Non-linear activation functions, e. g., Sigmoid, ReLU, and Tanh, have achieved great success in neural networks (NNs).

Disentanglement

Series Photo Selection via Multi-view Graph Learning

no code implementations18 Mar 2022 Jin Huang, Lu Zhang, Yongshun Gong, Jian Zhang, Xiushan Nie, Yilong Yin

Series photo selection (SPS) is an important branch of the image aesthetics quality assessment, which focuses on finding the best one from a series of nearly identical photos.

Aesthetics Quality Assessment Graph Learning

Sequential Multi-task Learning with Task Dependency for Appeal Judgment Prediction

no code implementations9 Mar 2022 Lianxin Song, Xiaohui Han, Guangqi Liu, Wentong Wang, Chaoran Cui, Yilong Yin

SMAJudge utilizes two sequential components to model the complete proceeding from the lower court to the appellate court and employs an attention mechanism to make the prediction more explainable, which handles the challenges of AJP effectively.

Multi-Task Learning

Exploring Domain-Invariant Parameters for Source Free Domain Adaptation

no code implementations CVPR 2022 Fan Wang, Zhongyi Han, Yongshun Gong, Yilong Yin

In contrast, we provide a fascinating insight: rather than attempting to learn domain-invariant representations, it is better to explore the domain-invariant parameters of the source model.

Privacy Preserving Source-Free Domain Adaptation

A Graph Matching Perspective With Transformers on Video Instance Segmentation

no code implementations CVPR 2022 Zheyun Qin, Xiankai Lu, Xiushan Nie, Yilong Yin, Jianbing Shen

Video Instance Segmentation (VIS) needs to automatically track and segment multiple objects in videos that rely on modeling the spatial-temporal interactions of the instances.

Graph Matching Instance Segmentation +2

Safe-Student for Safe Deep Semi-Supervised Learning With Unseen-Class Unlabeled Data

no code implementations CVPR 2022 Rundong He, Zhongyi Han, Xiankai Lu, Yilong Yin

To take advantage of these unseen-class data and ensure performance, we propose a safe SSL method called SAFE-STUDENT from the teacher-student view.

Learning to Rectify for Robust Learning with Noisy Labels

1 code implementation8 Nov 2021 Haoliang Sun, Chenhui Guo, Qi Wei, Zhongyi Han, Yilong Yin

In this paper, we propose warped probabilistic inference (WarPI) to achieve adaptively rectifying the training procedure for the classification network within the meta-learning scenario.

Learning with noisy labels Meta-Learning

Learning Transferable Parameters for Unsupervised Domain Adaptation

1 code implementation13 Aug 2021 Zhongyi Han, Haoliang Sun, Yilong Yin

However, the learning processes of domain-invariant features and source hypothesis inevitably involve domain-specific information that would degrade the generalizability of UDA models on the target domain.

Image Classification Keypoint Detection +2

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.

Image Segmentation Medical Image Segmentation +2

Tri-Branch Convolutional Neural Networks for Top-$k$ Focused Academic Performance Prediction

1 code implementation22 Jul 2021 Chaoran Cui, Jian Zong, Yuling Ma, Xinhua Wang, Lei Guo, Meng Chen, Yilong Yin

Academic performance prediction aims to leverage student-related information to predict their future academic outcomes, which is beneficial to numerous educational applications, such as personalized teaching and academic early warning.

Attentional Prototype Inference for Few-Shot Segmentation

1 code implementation14 May 2021 Haoliang Sun, Xiankai Lu, Haochen Wang, Yilong Yin, XianTong Zhen, Cees G. M. Snoek, Ling Shao

We define a global latent variable to represent the prototype of each object category, which we model as a probabilistic distribution.

Bayesian Inference Few-Shot Semantic Segmentation +2

MetaKernel: Learning Variational Random Features with Limited Labels

no code implementations8 May 2021 Yingjun Du, Haoliang Sun, XianTong Zhen, Jun Xu, Yilong Yin, Ling Shao, Cees G. M. Snoek

Specifically, we propose learning variational random features in a data-driven manner to obtain task-specific kernels by leveraging the shared knowledge provided by related tasks in a meta-learning setting.

Few-Shot Image Classification Few-Shot Learning +1

A Survey on Natural Language Video Localization

no code implementations1 Apr 2021 Xinfang Liu, Xiushan Nie, Zhifang Tan, Jie Guo, Yilong Yin

Natural language video localization (NLVL), which aims to locate a target moment from a video that semantically corresponds to a text query, is a novel and challenging task.

Direct Estimation of Spinal Cobb Angles by Structured Multi-Output Regression

no code implementations23 Dec 2020 Haoliang Sun, XianTong Zhen, Chris Bailey, Parham Rasoulinejad, Yilong Yin, Shuo Li

The Cobb angle that quantitatively evaluates the spinal curvature plays an important role in the scoliosis diagnosis and treatment.

regression

Attention Model Enhanced Network for Classification of Breast Cancer Image

no code implementations7 Oct 2020 Xiao Kang, Xingbo Liu, Xiushan Nie, Xiaoming Xi, Yilong Yin

In this study, we propose a novel method named Attention Model Enhanced Network (AMEN), which is formulated in a multi-branch fashion with pixel-wised attention model and classification submodular.

Classification General Classification

Learning Binary Semantic Embedding for Histology Image Classification and Retrieval

1 code implementation7 Oct 2020 Xiao Kang, Xingbo Liu, Xiushan Nie, Yilong Yin

With the development of medical imaging technology and machine learning, computer-assisted diagnosis which can provide impressive reference to pathologists, attracts extensive research interests.

Classification General Classification +2

Learning to Learn Kernels with Variational Random Features

1 code implementation ICML 2020 Xiantong Zhen, Haoliang Sun, Ying-Jun Du, Jun Xu, Yilong Yin, Ling Shao, Cees Snoek

We propose meta variational random features (MetaVRF) to learn adaptive kernels for the base-learner, which is developed in a latent variable model by treating the random feature basis as the latent variable.

Few-Shot Learning Variational Inference

Unifying Neural Learning and Symbolic Reasoning for Spinal Medical Report Generation

no code implementations28 Apr 2020 Zhongyi Han, Benzheng Wei, Yilong Yin, Shuo Li

In this paper, we propose the neural-symbolic learning (NSL) framework that performs human-like learning by unifying deep neural learning and symbolic logical reasoning for the spinal medical report generation.

Decision Making Generative Adversarial Network +3

Towards Accurate and Robust Domain Adaptation under Noisy Environments

1 code implementation27 Apr 2020 Zhongyi Han, Xian-Jin Gui, Chaoran Cui, Yilong Yin

In non-stationary environments, learning machines usually confront the domain adaptation scenario where the data distribution does change over time.

Unsupervised Domain Adaptation

Reinforcing Short-Length Hashing

no code implementations24 Apr 2020 Xingbo Liu, Xiushan Nie, Qi Dai, Yupan Huang, Yilong Yin

Due to the compelling efficiency in retrieval and storage, similarity-preserving hashing has been widely applied to approximate nearest neighbor search in large-scale image retrieval.

Image Retrieval Retrieval

PISEP^2: Pseudo Image Sequence Evolution based 3D Pose Prediction

no code implementations arXiv:1909.01818 2019 Xiaoli Liu, Jianqin Yin, Huaping Liu, Yilong Yin

Specifically, a skeletal representation is proposed by transforming the joint coordinate sequence into an image sequence, which can model the different correlations of different joints.

Computational Efficiency Pose Prediction

Mutual Linear Regression-based Discrete Hashing

no code implementations15 Mar 2019 Xingbo Liu, Xiushan Nie, Yilong Yin

Label information is widely used in hashing methods because of its effectiveness of improving the precision.

regression

Fusion Hashing: A General Framework for Self-improvement of Hashing

1 code implementation1 Oct 2018 Xingbo Liu, Xiushan Nie, Yilong Yin

In this paper, in contrast to existing hashing methods, we propose a novel generalized framework called fusion hashing (FH) to improve the precision of existing hashing methods without adding new constraints or penalty terms.

Data Structures and Algorithms Multimedia

Comprehensive Feature-based Robust Video Fingerprinting Using Tensor Model

no code implementations27 Jan 2016 Xiushan Nie, Yilong Yin, Jiande Sun

Therefore, in the present study, we mine the assistance and consensus among different features based on tensor model, and present a new comprehensive feature to fully use them in the proposed video fingerprinting framework.

Retrieval Tensor Decomposition

Cannot find the paper you are looking for? You can Submit a new open access paper.