Search Results for author: Yixuan Wu

Found 18 papers, 11 papers with code

PoCo: A Self-Supervised Approach via Polar Transformation Based Progressive Contrastive Learning for Ophthalmic Disease Diagnosis

no code implementations28 Mar 2024 Jinhong Wang, Tingting Chen, Jintai Chen, Yixuan Wu, Yuyang Xu, Danny Chen, Haochao Ying, Jian Wu

In this paper, we present a self-supervised method via polar transformation based progressive contrastive learning, called PoCo, for ophthalmic disease diagnosis.

Contrastive Learning

DetToolChain: A New Prompting Paradigm to Unleash Detection Ability of MLLM

no code implementations19 Mar 2024 Yixuan Wu, Yizhou Wang, Shixiang Tang, Wenhao Wu, Tong He, Wanli Ouyang, Jian Wu, Philip Torr

We present DetToolChain, a novel prompting paradigm, to unleash the zero-shot object detection ability of multimodal large language models (MLLMs), such as GPT-4V and Gemini.

Object object-detection +3

BlindDiff: Empowering Degradation Modelling in Diffusion Models for Blind Image Super-Resolution

1 code implementation15 Mar 2024 Feng Li, Yixuan Wu, Zichao Liang, Runmin Cong, Huihui Bai, Yao Zhao, Meng Wang

BlindDiff seamlessly integrates the MAP-based optimization into DMs, which constructs a joint distribution of the low-resolution (LR) observation, high-resolution (HR) data, and degradation kernels for the data and kernel priors, and solves the blind SR problem by unfolding MAP approach along with the reverse process.

Image Restoration Image Super-Resolution

AI-Enhanced Virtual Reality in Medicine: A Comprehensive Survey

no code implementations5 Feb 2024 Yixuan Wu, Kaiyuan Hu, Danny Z. Chen, Jian Wu

With the rapid advance of computer graphics and artificial intelligence technologies, the ways we interact with the world have undergone a transformative shift.

Medical Diagnosis

Hulk: A Universal Knowledge Translator for Human-Centric Tasks

2 code implementations4 Dec 2023 Yizhou Wang, Yixuan Wu, Shixiang Tang, Weizhen He, Xun Guo, Feng Zhu, Lei Bai, Rui Zhao, Jian Wu, Tong He, Wanli Ouyang

Human-centric perception tasks, e. g., pedestrian detection, skeleton-based action recognition, and pose estimation, have wide industrial applications, such as metaverse and sports analysis.

3D Human Pose Estimation Action Recognition +8

Assumption-lean and Data-adaptive Post-Prediction Inference

2 code implementations23 Nov 2023 Jiacheng Miao, Xinran Miao, Yixuan Wu, Jiwei Zhao, Qiongshi Lu

A primary challenge facing modern scientific research is the limited availability of gold-standard data which can be both costly and labor-intensive to obtain.


OneSeg: Self-learning and One-shot Learning based Single-slice Annotation for 3D Medical Image Segmentation

no code implementations24 Sep 2023 Yixuan Wu, Bo Zheng, Jintai Chen, Danny Z. Chen, Jian Wu

As deep learning methods continue to improve medical image segmentation performance, data annotation is still a big bottleneck due to the labor-intensive and time-consuming burden on medical experts, especially for 3D images.

Image Segmentation Medical Image Segmentation +5

GCL: Gradient-Guided Contrastive Learning for Medical Image Segmentation with Multi-Perspective Meta Labels

no code implementations16 Sep 2023 Yixuan Wu, Jintai Chen, Jiahuan Yan, Yiheng Zhu, Danny Z. Chen, Jian Wu

Since annotating medical images for segmentation tasks commonly incurs expensive costs, it is highly desirable to design an annotation-efficient method to alleviate the annotation burden.

Attribute Contrastive Learning +4

Described Object Detection: Liberating Object Detection with Flexible Expressions

2 code implementations NeurIPS 2023 Chi Xie, Zhao Zhang, Yixuan Wu, Feng Zhu, Rui Zhao, Shuang Liang

In this paper, we advance them to a more practical setting called Described Object Detection (DOD) by expanding category names to flexible language expressions for OVD and overcoming the limitation of REC only grounding the pre-existing object.

Binary Classification Described Object Detection +5

Advancing Referring Expression Segmentation Beyond Single Image

1 code implementation ICCV 2023 Yixuan Wu, Zhao Zhang, Xie Chi, Feng Zhu, Rui Zhao

To overcome this limitation, we propose a more realistic and general setting, named Group-wise Referring Expression Segmentation (GRES), which expands RES to a collection of related images, allowing the described objects to be present in a subset of input images.

Co-Salient Object Detection Object +4

MolHF: A Hierarchical Normalizing Flow for Molecular Graph Generation

1 code implementation15 May 2023 Yiheng Zhu, Zhenqiu Ouyang, Ben Liao, Jialu Wu, Yixuan Wu, Chang-Yu Hsieh, Tingjun Hou, Jian Wu

However, limited attention is paid to hierarchical generative models, which can exploit the inherent hierarchical structure (with rich semantic information) of the molecular graphs and generate complex molecules of larger size that we shall demonstrate to be difficult for most existing models.

Graph Generation Molecular Graph Generation +1

Gaussian Max-Value Entropy Search for Multi-Agent Bayesian Optimization

1 code implementation10 Mar 2023 Haitong Ma, Tianpeng Zhang, Yixuan Wu, Flavio P. Calmon, Na Li

We focus on Entropy Search (ES), a sample-efficient BO algorithm that selects queries to maximize the mutual information about the maximum of the black-box function.

Bayesian Optimization Computational Efficiency

Bridging Component Learning with Degradation Modelling for Blind Image Super-Resolution

1 code implementation3 Dec 2022 Yixuan Wu, Feng Li, Huihui Bai, Weisi Lin, Runmin Cong, Yao Zhao

In this paper, we analyze the degradation of a high-resolution (HR) image from image intrinsic components according to a degradation-based formulation model.

Image Super-Resolution

T2G-Former: Organizing Tabular Features into Relation Graphs Promotes Heterogeneous Feature Interaction

1 code implementation30 Nov 2022 Jiahuan Yan, Jintai Chen, Yixuan Wu, Danny Z. Chen, Jian Wu

Recent development of deep neural networks (DNNs) for tabular learning has largely benefited from the capability of DNNs for automatic feature interaction.


D-Former: A U-shaped Dilated Transformer for 3D Medical Image Segmentation

1 code implementation3 Jan 2022 Yixuan Wu, Kuanlun Liao, Jintai Chen, Jinhong Wang, Danny Z. Chen, Honghao Gao, Jian Wu

In this paper, we propose a new method called Dilated Transformer, which conducts self-attention for pair-wise patch relations captured alternately in local and global scopes.

Decoder Image Segmentation +3

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