Search Results for author: Ying Fu

Found 43 papers, 20 papers with code

Denoising Diffusion Semantic Segmentation with Mask Prior Modeling

1 code implementation2 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 Semantic Segmentation

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 Semantic Segmentation

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).


Hybrid Spectral Denoising Transformer with Learnable Query

1 code implementation16 Mar 2023 Zeqiang Lai, 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

no code implementations13 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

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

no code implementations10 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 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.


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.

Semi-Supervised Semantic Segmentation Weakly supervised Semantic Segmentation +1

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

6 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.


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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