Search Results for author: WeiJie Chen

Found 32 papers, 16 papers with code

Towards Precise 3D Human Pose Estimation with Multi-Perspective Spatial-Temporal Relational Transformers

1 code implementation30 Jan 2024 Jianbin Jiao, Xina Cheng, WeiJie Chen, Xiaoting Yin, Hao Shi, Kailun Yang

Due to the challenges in data collection, mainstream datasets of 3D human pose estimation are primarily composed of multi-view video data collected in laboratory environments, which contains rich spatial-temporal correlation information besides the image frame content.

3D Human Pose Estimation Scene Understanding

Parameter Exchange for Robust Dynamic Domain Generalization

1 code implementation23 Nov 2023 Luojun Lin, Zhifeng Shen, Zhishu Sun, Yuanlong Yu, Lei Zhang, WeiJie Chen

The parameters of dynamic networks can be decoupled into a static and a dynamic component, which are designed to learn domain-invariant and domain-specific features, respectively.

Disentanglement Domain Generalization

MetaFBP: Learning to Learn High-Order Predictor for Personalized Facial Beauty Prediction

1 code implementation23 Nov 2023 Luojun Lin, Zhifeng Shen, Jia-Li Yin, Qipeng Liu, Yuanlong Yu, WeiJie Chen

To this end, we propose a novel MetaFBP framework, in which we devise a universal feature extractor to capture the aesthetic commonality and then optimize to adapt the aesthetic individuality by shifting the decision boundary of the predictor via a meta-learning mechanism.

Facial Beauty Prediction Meta-Learning

Adapt Anything: Tailor Any Image Classifiers across Domains And Categories Using Text-to-Image Diffusion Models

no code implementations25 Oct 2023 WeiJie Chen, Haoyu Wang, Shicai Yang, Lei Zhang, Wei Wei, Yanning Zhang, Luojun Lin, Di Xie, Yueting Zhuang

Such a one-for-all adaptation paradigm allows us to adapt anything in the world using only one text-to-image generator as well as the corresponding unlabeled target data.

Domain Adaptation Image Classification

ACE-HetEM for ab initio Heterogenous Cryo-EM 3D Reconstruction

no code implementations9 Aug 2023 WeiJie Chen, Lin Yao, Zeqing Xia, Yuhang Wang

Unfortunately, standard amortized-inference-based methods with entangled latent spaces have difficulty learning the distribution of conformations and poses from cryo-EM images.

3D Reconstruction Disentanglement +1

FFF: Fragments-Guided Flexible Fitting for Building Complete Protein Structures

no code implementations7 Aug 2023 WeiJie Chen, Xinyan Wang, Yuhang Wang

This has inspired us to combine fragment recognition and structure prediction methods to build a complete structure.

Protein Structure Prediction

Adapting Pre-trained Language Models to Vision-Language Tasks via Dynamic Visual Prompting

1 code implementation1 Jun 2023 Shubin Huang, Qiong Wu, Yiyi Zhou, WeiJie Chen, Rongsheng Zhang, Xiaoshuai Sun, Rongrong Ji

In addition, we also experiment DVP with the recently popular adapter approach to keep the most parameters of PLMs intact when adapting to VL tasks, helping PLMs achieve a quick shift between single- and multi-modal tasks.

Transfer Learning Visual Prompting

Structure-CLIP: Towards Scene Graph Knowledge to Enhance Multi-modal Structured Representations

2 code implementations6 May 2023 Yufeng Huang, Jiji Tang, Zhuo Chen, Rongsheng Zhang, Xinfeng Zhang, WeiJie Chen, Zeng Zhao, Zhou Zhao, Tangjie Lv, Zhipeng Hu, Wen Zhang

In this paper, we present an end-to-end framework Structure-CLIP, which integrates Scene Graph Knowledge (SGK) to enhance multi-modal structured representations.

Image-text matching Text Matching

Twin support vector quantile regression

no code implementations6 May 2023 Yafen Ye, Zhihu Xu, Jinhua Zhang, WeiJie Chen, YuanHai Shao

We propose a twin support vector quantile regression (TSVQR) to capture the heterogeneous and asymmetric information in modern data.

regression Time Series

Multi-view Adversarial Discriminator: Mine the Non-causal Factors for Object Detection in Unseen Domains

1 code implementation CVPR 2023 Mingjun Xu, Lingyun Qin, WeiJie Chen, ShiLiang Pu, Lei Zhang

In this work, we present an idea to remove non-causal factors from common features by multi-view adversarial training on source domains, because we observe that such insignificant non-causal factors may still be significant in other latent spaces (views) due to the multi-mode structure of data.

Domain Generalization object-detection +1

1st Place Solution for ECCV 2022 OOD-CV Challenge Object Detection Track

no code implementations12 Jan 2023 Wei Zhao, Binbin Chen, WeiJie Chen, Shicai Yang, Di Xie, ShiLiang Pu, Yueting Zhuang

The domain adaptation part is implemented as a Source-Free Domain Adaptation paradigm, which only uses the pre-trained model and the unlabeled target data to further optimize in a self-supervised training manner.

Domain Generalization object-detection +3

1st Place Solution for ECCV 2022 OOD-CV Challenge Image Classification Track

no code implementations12 Jan 2023 Yilu Guo, Xingyue Shi, WeiJie Chen, Shicai Yang, Di Xie, ShiLiang Pu, Yueting Zhuang

In the test-time training stage, we use the pre-trained model to assign noisy label for the unlabeled target data, and propose a Label-Periodically-Updated DivideMix method for noisy label learning.

Data Augmentation Domain Generalization +2

FFF: Fragment-Guided Flexible Fitting for Building Complete Protein Structures

no code implementations CVPR 2023 WeiJie Chen, Xinyan Wang, Yuhang Wang

This has inspired us to combine fragment recognition and structure prediction methods to build a complete structure.

Protein Structure Prediction

Unsupervised Prompt Tuning for Text-Driven Object Detection

no code implementations ICCV 2023 Weizhen He, WeiJie Chen, Binbin Chen, Shicai Yang, Di Xie, Luojun Lin, Donglian Qi, Yueting Zhuang

In this paper, we delve into this problem and propose an Unsupervised Prompt Tuning framework for text-driven object detection, which is composed of two novel mean teaching mechanisms.

Data Augmentation Object +4

Informing selection of performance metrics for medical image segmentation evaluation using configurable synthetic errors

no code implementations30 Dec 2022 Shuyue Guan, Ravi K. Samala, WeiJie Chen

By analyzing the intrinsic properties of these metrics and categorizing the segmentation errors, we are working toward the goal of developing a decision-tree tool for assisting in the selection of segmentation performance metrics.

Image Segmentation Medical Image Segmentation +2

Attention Diversification for Domain Generalization

1 code implementation9 Oct 2022 Rang Meng, Xianfeng Li, WeiJie Chen, Shicai Yang, Jie Song, Xinchao Wang, Lei Zhang, Mingli Song, Di Xie, ShiLiang Pu

Under this guidance, a novel Attention Diversification framework is proposed, in which Intra-Model and Inter-Model Attention Diversification Regularization are collaborated to reassign appropriate attention to diverse task-related features.

Domain Generalization

Universal Domain Adaptive Object Detector

no code implementations5 Jul 2022 Wenxu Shi, Lei Zhang, WeiJie Chen, ShiLiang Pu

Universal domain adaptive object detection (UniDAOD)is more challenging than domain adaptive object detection (DAOD) since the label space of the source domain may not be the same as that of the target and the scale of objects in the universal scenarios can vary dramatically (i. e, category shift and scale shift).

Multi-Label Learning Object +2

Unraveling the Mystery of Artifacts in Machine Generated Text

1 code implementation LREC 2022 Jiashu Pu, Ziyi Huang, Yadong Xi, Guandan Chen, WeiJie Chen, Rongsheng Zhang

As neural Text Generation Models (TGM) have become more and more capable of generating text indistinguishable from human-written ones, the misuse of text generation technologies can have serious ramifications.

Text Generation

Label Matching Semi-Supervised Object Detection

3 code implementations CVPR 2022 Binbin Chen, WeiJie Chen, Shicai Yang, Yunyi Xuan, Jie Song, Di Xie, ShiLiang Pu, Mingli Song, Yueting Zhuang

To remedy this issue, we present a novel label assignment mechanism for self-training framework, namely proposal self-assignment, which injects the proposals from student into teacher and generates accurate pseudo labels to match each proposal in the student model accordingly.

Object object-detection +2

Slimmable Domain Adaptation

1 code implementation CVPR 2022 Rang Meng, WeiJie Chen, Shicai Yang, Jie Song, Luojun Lin, Di Xie, ShiLiang Pu, Xinchao Wang, Mingli Song, Yueting Zhuang

In this paper, we introduce a simple framework, Slimmable Domain Adaptation, to improve cross-domain generalization with a weight-sharing model bank, from which models of different capacities can be sampled to accommodate different accuracy-efficiency trade-offs.

Domain Generalization Unsupervised Domain Adaptation

Transductive CLIP with Class-Conditional Contrastive Learning

no code implementations13 Jun 2022 Junchu Huang, WeiJie Chen, Shicai Yang, Di Xie, ShiLiang Pu, Yueting Zhuang

This framework can reduce the impact of noisy labels from CLIP model effectively by combining both techniques.

Contrastive Learning Pseudo Label +1

Learning Domain Adaptive Object Detection with Probabilistic Teacher

2 code implementations13 Jun 2022 Meilin Chen, WeiJie Chen, Shicai Yang, Jie Song, Xinchao Wang, Lei Zhang, Yunfeng Yan, Donglian Qi, Yueting Zhuang, Di Xie, ShiLiang Pu

In addition, we conduct anchor adaptation in parallel with localization adaptation, since anchor can be regarded as a learnable parameter.

Object object-detection +1

Dynamic Domain Generalization

1 code implementation27 May 2022 Zhishu Sun, Zhifeng Shen, Luojun Lin, Yuanlong Yu, Zhifeng Yang, Shicai Yang, WeiJie Chen

Specifically, we leverage a meta-adjuster to twist the network parameters based on the static model with respect to different data from different domains.

Domain Generalization

Probing Simile Knowledge from Pre-trained Language Models

1 code implementation ACL 2022 WeiJie Chen, Yongzhu Chang, Rongsheng Zhang, Jiashu Pu, Guandan Chen, Le Zhang, Yadong Xi, Yijiang Chen, Chang Su

In this paper, we probe simile knowledge from PLMs to solve the SI and SG tasks in the unified framework of simile triple completion for the first time.

Language Modelling Position +1

Semi-Supervised Domain Generalization with Evolving Intermediate Domain

1 code implementation19 Nov 2021 Luojun Lin, Han Xie, Zhishu Sun, WeiJie Chen, Wenxi Liu, Yuanlong Yu, Lei Zhang

From this perspective, we introduce a novel paradigm of DG, termed as Semi-Supervised Domain Generalization (SSDG), to explore how the labeled and unlabeled source domains can interact, and establish two settings, including the close-set and open-set SSDG.

Domain Generalization Semi-Supervised Domain Generalization

A Stochastic Composite Augmented Lagrangian Method For Reinforcement Learning

no code implementations20 May 2021 Yongfeng Li, Mingming Zhao, WeiJie Chen, Zaiwen Wen

A general theoretical analysis shows that the solutions generated from a sequence of the constrained optimizations converge to the optimal solution of the LP if the error is controlled properly.

reinforcement-learning Reinforcement Learning (RL)

Self-Supervised Noisy Label Learning for Source-Free Unsupervised Domain Adaptation

no code implementations23 Feb 2021 WeiJie Chen, Luojun Lin, Shicai Yang, Di Xie, ShiLiang Pu, Yueting Zhuang, Wenqi Ren

Usually, the given source domain pre-trained model is expected to optimize with only unlabeled target data, which is termed as source-free unsupervised domain adaptation.

Self-Supervised Learning Unsupervised Domain Adaptation

DP-GEN: A concurrent learning platform for the generation of reliable deep learning based potential energy models

1 code implementation28 Oct 2019 Yuzhi Zhang, Haidi Wang, WeiJie Chen, Jinzhe Zeng, Linfeng Zhang, Han Wang, Weinan E

Materials 3, 023804] and is capable of generating uniformly accurate deep learning based PES models in a way that minimizes human intervention and the computational cost for data generation and model training.

Computational Physics

Fast and Robust Rank Aggregation against Model Misspecification

1 code implementation29 May 2019 Yuangang Pan, WeiJie Chen, Gang Niu, Ivor W. Tsang, Masashi Sugiyama

Specifically, the properties of our CoarsenRank are summarized as follows: (1) CoarsenRank is designed for mild model misspecification, which assumes there exist the ideal preferences (consistent with model assumption) that locates in a neighborhood of the actual preferences.

Bayesian Inference

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