Search Results for author: Ying Fu

Found 66 papers, 33 papers with code

LLMs Instruct LLMs:An Extraction and Editing Method

no code implementations23 Mar 2024 Xin Zhang, Tianjie Ju, Huijia Liang, Ying Fu, Qin Zhang

The interest in updating Large Language Models (LLMs) without retraining from scratch is substantial, yet it comes with some challenges. This is especially true for situations demanding complex reasoning with limited samples, a scenario we refer to as the Paucity-Constrained Complex Reasoning Adaptation for LLMs (PCRA-LLM). Traditional methods like Low-Rank Adaptation (LoRA) and Retrieval-Augmented Generation (RAG) are inadequate for this critical issue, particularly evident in our exploration of a specific medical context that epitomize the PCRA-LLM's distinct needs. To address the issue, we propose a Sequential Fusion method to incorporate knowledge from complex context into LLMs.

Knowledge Graphs Question Answering

Safeguarding Medical Image Segmentation Datasets against Unauthorized Training via Contour- and Texture-Aware Perturbations

no code implementations21 Mar 2024 Xun Lin, Yi Yu, Song Xia, Jue Jiang, Haoran Wang, Zitong Yu, Yizhong Liu, Ying Fu, Shuai Wang, Wenzhong Tang, Alex Kot

This is particularly true for medical image segmentation (MIS) datasets, where the processes of collection and fine-grained annotation are time-intensive and laborious.

Image Classification Image Generation +4

When Semantic Segmentation Meets Frequency Aliasing

1 code implementation14 Mar 2024 Linwei Chen, Lin Gu, Ying Fu

While positively correlated with the proposed aliasing score, three types of hard pixels exhibit different patterns.

De-aliasing Instance Segmentation +2

Frequency-Adaptive Dilated Convolution for Semantic Segmentation

1 code implementation8 Mar 2024 Linwei Chen, Lin Gu, Ying Fu

Dilated convolution, which expands the receptive field by inserting gaps between its consecutive elements, is widely employed in computer vision.

object-detection Object Detection +1

Degradation Modeling and Prognostic Analysis Under Unknown Failure Modes

1 code implementation29 Feb 2024 Ying Fu, Ye Kwon Huh, Kaibo Liu

Then, using these degradation trajectories, we develop a time series-based clustering method to identify the training units' failure modes.

Dimensionality Reduction

Masked Conditional Diffusion Model for Enhancing Deepfake Detection

no code implementations1 Feb 2024 Tiewen Chen, Shanmin Yang, Shu Hu, Zhenghan Fang, Ying Fu, Xi Wu, Xin Wang

this paper present we put a new insight into diffusion model-based data augmentation, and propose a Masked Conditional Diffusion Model (MCDM) for enhancing deepfake detection.

Data Augmentation DeepFake Detection +1

Comparative Study on the Performance of Categorical Variable Encoders in Classification and Regression Tasks

1 code implementation18 Jan 2024 Wenbin Zhu, Runwen Qiu, Ying Fu

This study broadly classifies machine learning models into three categories: 1) ATI models that implicitly perform affine transformations on inputs, such as multi-layer perceptron neural network; 2) Tree-based models that are based on decision trees, such as random forest; and 3) the rest, such as kNN.

Fraud Detection

CascadeV-Det: Cascade Point Voting for 3D Object Detection

1 code implementation15 Jan 2024 Yingping Liang, Ying Fu

Additionally, since model training can suffer from a lack of proposal points with high centerness, we have developed the CPA module to narrow down the positive assignment threshold with cascade stages.

3D Object Detection Object +1

Atlantis: Enabling Underwater Depth Estimation with Stable Diffusion

1 code implementation19 Dec 2023 Fan Zhang, ShaoDi You, Yu Li, Ying Fu

Nonetheless, the performance of these methods is often constrained by the domain gap and looser constraints.

Monocular Depth Estimation Style Transfer +1

Latent Diffusion Prior Enhanced Deep Unfolding for Spectral Image Reconstruction

no code implementations24 Nov 2023 Zongliang Wu, Ruiying Lu, Ying Fu, Xin Yuan

Snapshot compressive spectral imaging reconstruction aims to reconstruct three-dimensional spatial-spectral images from a single-shot two-dimensional compressed measurement.

Computational Efficiency Image Reconstruction +1

Siamese-DETR for Generic Multi-Object Tracking

no code implementations27 Oct 2023 Qiankun Liu, Yichen Li, Yuqi Jiang, Ying Fu

Recently, Open-Vocabulary MOT (OVMOT) and Generic MOT (GMOT) are proposed to track interested objects beyond pre-defined categories with the given text prompt and template image.

Autonomous Driving Language Modelling +3

Biomedical Image Splicing Detection using Uncertainty-Guided Refinement

no code implementations28 Sep 2023 Xun Lin, Wenzhong Tang, Shuai Wang, Zitong Yu, Yizhong Liu, Haoran Wang, Ying Fu, Alex Kot

Besides, we construct a dataset for Biomedical image Splicing (BioSp) detection, which consists of 1, 290 spliced images.

Image Forensics Image Manipulation

MPI-Flow: Learning Realistic Optical Flow with Multiplane Images

1 code implementation ICCV 2023 Yingping Liang, Jiaming Liu, Debing Zhang, Ying Fu

The accuracy of learning-based optical flow estimation models heavily relies on the realism of the training datasets.

Optical Flow Estimation

RawHDR: High Dynamic Range Image Reconstruction from a Single Raw Image

1 code implementation ICCV 2023 Yunhao Zou, Chenggang Yan, Ying Fu

Unlike existing methods, the core idea of this work is to incorporate more informative Raw sensor data to generate HDR images, aiming to recover scene information in hard regions (the darkest and brightest areas of an HDR scene).

HDR Reconstruction Image Reconstruction

Recurrent Self-Supervised Video Denoising with Denser Receptive Field

no code implementations7 Aug 2023 Zichun Wang, Yulun Zhang, Debing Zhang, Ying Fu

However, under their blind spot constraints, previous self-supervised video denoising methods suffer from significant information loss and texture destruction in either the whole reference frame or neighbor frames, due to their inadequate consideration of the receptive field.

Denoising Video Denoising

Denoising Diffusion Semantic Segmentation with Mask Prior Modeling

no code implementations2 Jun 2023 Zeqiang Lai, Yuchen Duan, Jifeng Dai, Ziheng Li, Ying Fu, Hongsheng Li, Yu Qiao, Wenhai Wang

In this paper, we propose to ameliorate the semantic segmentation quality of existing discriminative approaches with a mask prior modeled by a recently-developed denoising diffusion generative model.

Denoising Segmentation +1

Instance Segmentation in the Dark

1 code implementation27 Apr 2023 Linwei Chen, Ying Fu, Kaixuan Wei, Dezhi Zheng, Felix Heide

Existing instance segmentation techniques are primarily tailored for high-visibility inputs, but their performance significantly deteriorates in extremely low-light environments.

Instance Segmentation Object Detection +2

Spectral Enhanced Rectangle Transformer for Hyperspectral Image Denoising

1 code implementation CVPR 2023 Miaoyu Li, Ji Liu, Ying Fu, Yulun Zhang, Dejing Dou

In this paper, we address these issues by proposing a spectral enhanced rectangle Transformer, driving it to explore the non-local spatial similarity and global spectral low-rank property of HSIs.

Hyperspectral Image Denoising Image Denoising

LG-BPN: Local and Global Blind-Patch Network for Self-Supervised Real-World Denoising

1 code implementation CVPR 2023 Zichun Wang, Ying Fu, Ji Liu, Yulun Zhang

Despite the significant results on synthetic noise under simplified assumptions, most self-supervised denoising methods fail under real noise due to the strong spatial noise correlation, including the advanced self-supervised blind-spot networks (BSNs).

Denoising

Hybrid Spectral Denoising Transformer with Guided Attention

1 code implementation ICCV 2023 Zeqiang Lai, Chenggang Yan, Ying Fu

Challenges in adapting transformer for HSI arise from the capabilities to tackle existing limitations of CNN-based methods in capturing the global and local spatial-spectral correlations while maintaining efficiency and flexibility.

Hyperspectral Image Denoising Image Denoising

HyperAttack: Multi-Gradient-Guided White-box Adversarial Structure Attack of Hypergraph Neural Networks

no code implementations24 Feb 2023 Chao Hu, Ruishi Yu, Binqi Zeng, Yu Zhan, Ying Fu, Quan Zhang, Rongkai Liu, Heyuan Shi

Hypergraph neural networks (HGNN) have shown superior performance in various deep learning tasks, leveraging the high-order representation ability to formulate complex correlations among data by connecting two or more nodes through hyperedge modeling.

Adversarial Attack

Hyperspectral Image Super Resolution with Real Unaligned RGB Guidance

1 code implementation13 Feb 2023 Zeqiang Lai, Ying Fu, Jun Zhang

The features of RGB reference images are then processed by a multi-stage alignment module to explicitly align the features of RGB reference with the LR HSI.

Hyperspectral Image Super-Resolution Image Super-Resolution

Mixed Attention Network for Hyperspectral Image Denoising

1 code implementation27 Jan 2023 Zeqiang Lai, Ying Fu

However, existing methods show limitations in exploring the spectral correlations across different bands and feature interactions within each band.

Hyperspectral Image Denoising Image Denoising

Visible-Infrared Person Re-Identification via Semantic Alignment and Affinity Inference

1 code implementation ICCV 2023 Xingye Fang, Yang Yang, Ying Fu

We propose a Semantic Alignment and Affinity Inference framework (SAAI), which aims to align latent semantic part features with the learnable prototypes and improve inference with affinity information.

Person Re-Identification

Iterative Denoiser and Noise Estimator for Self-Supervised Image Denoising

no code implementations ICCV 2023 Yunhao Zou, Chenggang Yan, Ying Fu

However, the unavailable noise prior and inefficient feature extraction take these methods away from high practicality and precision.

Image Denoising

Fine-grained Unsupervised Domain Adaptation for Gait Recognition

no code implementations ICCV 2023 Kang Ma, Ying Fu, Dezhi Zheng, Yunjie Peng, Chunshui Cao, Yongzhen Huang

Gait recognition has emerged as a promising technique for the long-range retrieval of pedestrians, providing numerous advantages such as accurate identification in challenging conditions and non-intrusiveness, making it highly desirable for improving public safety and security.

Gait Recognition Unsupervised Domain Adaptation

Learning Rain Location Prior for Nighttime Deraining

1 code implementation ICCV 2023 Fan Zhang, ShaoDi You, Yu Li, Ying Fu

This learned prior contains location information of rain streaks and, when injected into deraining models, can significantly improve their performance.

Rain Removal

Dynamic Aggregated Network for Gait Recognition

no code implementations CVPR 2023 Kang Ma, Ying Fu, Dezhi Zheng, Chunshui Cao, Xuecai Hu, Yongzhen Huang

Specifically, we create a dynamic attention mechanism between the features of neighboring pixels that not only adaptively focuses on key regions but also generates more expressive local motion patterns.

Gait Recognition

Improved Quasi-Recurrent Neural Network for Hyperspectral Image Denoising

no code implementations27 Nov 2022 Zeqiang Lai, Ying Fu

Hyperspectral image is unique and useful for its abundant spectral bands, but it subsequently requires extra elaborated treatments of the spatial-spectral correlation as well as the global correlation along the spectrum for building a robust and powerful HSI restoration algorithm.

Hyperspectral Image Denoising Image Denoising

GTAV-NightRain: Photometric Realistic Large-scale Dataset for Night-time Rain Streak Removal

1 code implementation10 Oct 2022 Fan Zhang, ShaoDi You, Yu Li, Ying Fu

In this paper, we propose GTAV-NightRain dataset, which is a large-scale synthetic night-time rain streak removal dataset.

Deep Plug-and-Play Prior for Hyperspectral Image Restoration

1 code implementation17 Sep 2022 Zeqiang Lai, Kaixuan Wei, Ying Fu

Deep-learning-based hyperspectral image (HSI) restoration methods have gained great popularity for their remarkable performance but often demand expensive network retraining whenever the specifics of task changes.

Denoising Hyperspectral Image Denoising +2

ProbNVS: Fast Novel View Synthesis with Learned Probability-Guided Sampling

no code implementations7 Apr 2022 Yuemei Zhou, Tao Yu, Zerong Zheng, Ying Fu, Yebin Liu

Existing state-of-the-art novel view synthesis methods rely on either fairly accurate 3D geometry estimation or sampling of the entire space for neural volumetric rendering, which limit the overall efficiency.

Novel View Synthesis

Estimating Fine-Grained Noise Model via Contrastive Learning

no code implementations CVPR 2022 Yunhao Zou, Ying Fu

In this work, we combine both noise modeling and estimation, and propose an innovative noise model estimation and noise synthesis pipeline for realistic noisy image generation.

Contrastive Learning Image Denoising +2

End-to-End Video Text Spotting with Transformer

1 code implementation20 Mar 2022 Weijia Wu, Yuanqiang Cai, Chunhua Shen, Debing Zhang, Ying Fu, Hong Zhou, Ping Luo

Recent video text spotting methods usually require the three-staged pipeline, i. e., detecting text in individual images, recognizing localized text, tracking text streams with post-processing to generate final results.

Text Detection Text Spotting

Mutual Contrastive Low-rank Learning to Disentangle Whole Slide Image Representations for Glioma Grading

no code implementations8 Mar 2022 Lipei Zhang, Yiran Wei, Ying Fu, Stephen Price, Carola-Bibiane Schönlieb, Chao Li

In this proposed scheme, we design a normalized modality contrastive loss (NMC-loss), which could promote to disentangle multi-modality complementary representation of FFPE and frozen sections from the same patient.

Contrastive Learning Disentanglement +1

Dynamic Proximal Unrolling Network for Compressive Imaging

no code implementations23 Jul 2021 Yixiao Yang, Ran Tao, Kaixuan Wei, Ying Fu

In this paper, a dynamic proximal unrolling network (dubbed DPUNet) was proposed, which can handle a variety of measurement matrices via one single model without retraining.

Compressive Sensing Rolling Shutter Correction

Learning Temporal Consistency for Low Light Video Enhancement From Single Images

1 code implementation CVPR 2021 Fan Zhang, Yu Li, ShaoDi You, Ying Fu

Based on this idea, we propose our method which can infer motion prior for single image low light video enhancement and enforce temporal consistency.

Optical Flow Estimation Video Enhancement

LocalTrans: A Multiscale Local Transformer Network for Cross-Resolution Homography Estimation

no code implementations ICCV 2021 Ruizhi Shao, Gaochang Wu, Yuemei Zhou, Ying Fu, Yebin Liu

By combining the local transformer with the multiscale structure, the network is able to capture long-short range correspondences efficiently and accurately.

Homography Estimation

Disentangled Face Attribute Editing via Instance-Aware Latent Space Search

1 code implementation26 May 2021 Yuxuan Han, Jiaolong Yang, Ying Fu

We further propose a Disentanglement-Transformation (DT) metric to quantify the attribute transformation and disentanglement efficacy and find the optimal control factor between attribute-level and instance-specific directions based on it.

Attribute Disentanglement

Probing quasi-long-range ordering by magnetostriction in monolayer CoPS3

no code implementations4 Jan 2021 Qiye Liu, Le Wang, Ying Fu, Xi Zhang, Lianglong Huang, Huimin Su, Junhao Lin, Xiaobin Chen, Dapeng Yu, Xiaodong Cui, Jia-Wei Mei, Jun-Feng Dai

Mermin-Wagner-Coleman theorem predicts no long-range magnetic order at finite temperature in the two-dimensional (2D) isotropic systems, but a quasi-long-range order with a divergent correlation length at the Kosterlitz-Thouless (KT) transition for planar magnets.

Mesoscale and Nanoscale Physics

Hyperspectral Image Denoising With Realistic Data

1 code implementation ICCV 2021 Tao Zhang, Ying Fu, Cheng Li

On the other hand, we propose an accurate HSI noise model which matches the distribution of real data well and can be employed to synthesize realistic dataset.

Hyperspectral Image Denoising Image Denoising

Weakly-supervised Semantic Segmentation in Cityscape via Hyperspectral Image

no code implementations18 Dec 2020 Yuxing Huang, ShaoDi You, Ying Fu, Qiu Shen

It is based on the idea that high-resolution HSIs in city scenes contain rich spectral information, which can be easily associated to semantics without manual labeling.

Segmentation Semi-Supervised Semantic Segmentation +2

GPS-Net: Graph-based Photometric Stereo Network

no code implementations NeurIPS 2020 Zhuokun Yao, Kun Li, Ying Fu, Haofeng Hu, Boxin Shi

For all-pixel operation, we propose the Normal Regression Network to make efficient use of the intra-image spatial information for predicting a surface normal map with rich details.

Cross-MPI: Cross-scale Stereo for Image Super-Resolution using Multiplane Images

no code implementations CVPR 2021 Yuemei Zhou, Gaochang Wu, Ying Fu, Kun Li, Yebin Liu

Various combinations of cameras enrich computational photography, among which reference-based superresolution (RefSR) plays a critical role in multiscale imaging systems.

Image Super-Resolution

TFPnP: Tuning-free Plug-and-Play Proximal Algorithm with Applications to Inverse Imaging Problems

1 code implementation18 Nov 2020 Kaixuan Wei, Angelica Aviles-Rivero, Jingwei Liang, Ying Fu, Hua Huang, Carola-Bibiane Schönlieb

In this work, we present a class of tuning-free PnP proximal algorithms that can determine parameters such as denoising strength, termination time, and other optimization-specific parameters automatically.

Denoising Retrieval

Partial FC: Training 10 Million Identities on a Single Machine

7 code implementations11 Oct 2020 Xiang An, Xuhan Zhu, Yang Xiao, Lan Wu, Ming Zhang, Yuan Gao, Bin Qin, Debing Zhang, Ying Fu

The experiment demonstrates no loss of accuracy when training with only 10\% randomly sampled classes for the softmax-based loss functions, compared with training with full classes using state-of-the-art models on mainstream benchmarks.

Face Identification Face Recognition +2

EasyQuant: Post-training Quantization via Scale Optimization

1 code implementation30 Jun 2020 Di Wu, Qi Tang, Yongle Zhao, Ming Zhang, Ying Fu, Debing Zhang

The 8 bits quantization has been widely applied to accelerate network inference in various deep learning applications.

Quantization

A Physics-based Noise Formation Model for Extreme Low-light Raw Denoising

1 code implementation CVPR 2020 Kaixuan Wei, Ying Fu, Jiaolong Yang, Hua Huang

Lacking rich and realistic data, learned single image denoising algorithms generalize poorly to real raw images that do not resemble the data used for training.

Image Denoising

3D Quasi-Recurrent Neural Network for Hyperspectral Image Denoising

2 code implementations10 Mar 2020 Kaixuan Wei, Ying Fu, Hua Huang

In this paper, we propose an alternating directional 3D quasi-recurrent neural network for hyperspectral image (HSI) denoising, which can effectively embed the domain knowledge -- structural spatio-spectral correlation and global correlation along spectrum.

Hyperspectral Image Denoising Image Denoising

Tuning-free Plug-and-Play Proximal Algorithm for Inverse Imaging Problems

1 code implementation ICML 2020 Kaixuan Wei, Angelica Aviles-Rivero, Jingwei Liang, Ying Fu, Carola-Bibiane Schönlieb, Hua Huang

Moreover, we discuss the practical considerations of the plugged denoisers, which together with our learned policy yield state-of-the-art results.

Denoising Retrieval

Hyperspectral City V1.0 Dataset and Benchmark

no code implementations24 Jul 2019 Shaodi You, Erqi Huang, Shuaizhe Liang, Yongrong Zheng, Yunxiang Li, Fan Wang, Sen Lin, Qiu Shen, Xun Cao, Diming Zhang, Yuanjiang Li, Yu Li, Ying Fu, Boxin Shi, Feng Lu, Yinqiang Zheng, Robby T. Tan

This document introduces the background and the usage of the Hyperspectral City Dataset and the benchmark.

Hyperspectral Image Super-Resolution With Optimized RGB Guidance

no code implementations CVPR 2019 Ying Fu, Tao Zhang, Yinqiang Zheng, Debing Zhang, Hua Huang

To overcome the limitations of existing hyperspectral cameras on spatial/temporal resolution, fusing a low resolution hyperspectral image (HSI) with a high resolution RGB (or multispectral) image into a high resolution HSI has been prevalent.

Hyperspectral Image Super-Resolution Image Super-Resolution

Single Image Reflection Removal Exploiting Misaligned Training Data and Network Enhancements

1 code implementation CVPR 2019 Kaixuan Wei, Jiaolong Yang, Ying Fu, David Wipf, Hua Huang

Removing undesirable reflections from a single image captured through a glass window is of practical importance to visual computing systems.

Reflection Removal

Joint Camera Spectral Sensitivity Selection and Hyperspectral Image Recovery

no code implementations ECCV 2018 Ying Fu, Tao Zhang, Yinqiang Zheng, Debing Zhang, Hua Huang

Hyperspectral image (HSI) recovery from a single RGB image has attracted much attention, whose performance has recently been shown to be sensitive to the camera spectral sensitivity (CSS).

Image Restoration from Patch-based Compressed Sensing Measurement

no code implementations2 Jun 2017 Guangtao Nie, Ying Fu, Yinqiang Zheng, Hua Huang

A series of methods have been proposed to reconstruct an image from compressively sensed random measurement, but most of them have high time complexity and are inappropriate for patch-based compressed sensing capture, because of their serious blocky artifacts in the restoration results.

Compressive Sensing Image Reconstruction +1

Exploiting Spectral-Spatial Correlation for Coded Hyperspectral Image Restoration

no code implementations CVPR 2016 Ying Fu, Yinqiang Zheng, Imari Sato, Yoichi Sato

In this paper, we propose an effective method for coded hyperspectral image restoration, which exploits extensive structure sparsity in the hyperspectral image.

Image Restoration

Adaptive Spatial-Spectral Dictionary Learning for Hyperspectral Image Denoising

no code implementations ICCV 2015 Ying Fu, Antony Lam, Imari Sato, Yoichi Sato

Hyperspectral imaging is beneficial in a diverse range of applications from diagnostic medicine, to agriculture, to surveillance to name a few.

Dictionary Learning Hyperspectral Image Denoising +1

Separating Fluorescent and Reflective Components by Using a Single Hyperspectral Image

no code implementations ICCV 2015 Yinqiang Zheng, Ying Fu, Antony Lam, Imari Sato, Yoichi Sato

This paper introduces a novel method to separate fluorescent and reflective components in the spectral domain.

Reflectance and Fluorescent Spectra Recovery based on Fluorescent Chromaticity Invariance under Varying Illumination

no code implementations CVPR 2014 Ying Fu, Antony Lam, Yasuyuki Kobashi, Imari Sato, Takahiro Okabe, Yoichi Sato

We then show that given the spectral reflectance and fluorescent chromaticity, the fluorescence absorption and emission spectra can also be estimated.

3D Reconstruction

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