Search Results for author: Lin Gu

Found 39 papers, 21 papers with code

Feature Normalized Knowledge Distillation for Image Classification

1 code implementation ECCV 2020 Kunran Xu, Lai Rui, Yishi Li, Lin Gu

From this perspective, we systematically analyze the distillation mechanism and demonstrate that the L2-norm of the feature in penultimate layer would be too large under the influence of label noise, and the temperature T in KD could be regarded as a correction factor for L2-norm to suppress the impact of noise.

Classification General Classification +2

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

Robust Synthetic-to-Real Transfer for Stereo Matching

1 code implementation12 Mar 2024 Jiawei Zhang, Jiahe Li, Lei Huang, Xiaohan Yu, Lin Gu, Jin Zheng, Xiao Bai

With advancements in domain generalized stereo matching networks, models pre-trained on synthetic data demonstrate strong robustness to unseen domains.

Domain Generalization Pseudo Label +1

DNGaussian: Optimizing Sparse-View 3D Gaussian Radiance Fields with Global-Local Depth Normalization

1 code implementation11 Mar 2024 Jiahe Li, Jiawei Zhang, Xiao Bai, Jin Zheng, Xin Ning, Jun Zhou, Lin Gu

Our motivation stems from the highly efficient representation and surprising quality of the recent 3D Gaussian Splatting, despite it will encounter a geometry degradation when input views decrease.

Novel View Synthesis

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

Aleth-NeRF: Illumination Adaptive NeRF with Concealing Field Assumption

1 code implementation14 Dec 2023 Ziteng Cui, Lin Gu, Xiao Sun, Xianzheng Ma, Yu Qiao, Tatsuya Harada

The standard Neural Radiance Fields (NeRF) paradigm employs a viewer-centered methodology, entangling the aspects of illumination and material reflectance into emission solely from 3D points.

Expert Uncertainty and Severity Aware Chest X-Ray Classification by Multi-Relationship Graph Learning

no code implementations6 Sep 2023 Mengliang Zhang, Xinyue Hu, Lin Gu, Liangchen Liu, Kazuma Kobayashi, Tatsuya Harada, Ronald M. Summers, Yingying Zhu

In this paper, we re-extract disease labels from CXR reports to make them more realistic by considering disease severity and uncertainty in classification.

Graph Learning

SRMAE: Masked Image Modeling for Scale-Invariant Deep Representations

no code implementations17 Aug 2023 Zhiming Wang, Lin Gu, Feng Lu

Our method also achieves an accuracy of 74. 84% on the task of recognizing low-resolution facial expressions, surpassing the current state-of-the-art FMD by 9. 48%.

Super-Resolution

Efficient Region-Aware Neural Radiance Fields for High-Fidelity Talking Portrait Synthesis

1 code implementation ICCV 2023 Jiahe Li, Jiawei Zhang, Xiao Bai, Jun Zhou, Lin Gu

This paper presents ER-NeRF, a novel conditional Neural Radiance Fields (NeRF) based architecture for talking portrait synthesis that can concurrently achieve fast convergence, real-time rendering, and state-of-the-art performance with small model size.

Aleth-NeRF: Low-light Condition View Synthesis with Concealing Fields

1 code implementation10 Mar 2023 Ziteng Cui, Lin Gu, Xiao Sun, Xianzheng Ma, Yu Qiao, Tatsuya Harada

Common capture low-light scenes are challenging for most computer vision techniques, including Neural Radiance Fields (NeRF).

Sketch-based Medical Image Retrieval

1 code implementation7 Mar 2023 Kazuma Kobayashi, Lin Gu, Ryuichiro Hataya, Takaaki Mizuno, Mototaka Miyake, Hirokazu Watanabe, Masamichi Takahashi, Yasuyuki Takamizawa, Yukihiro Yoshida, Satoshi Nakamura, Nobuji Kouno, Amina Bolatkan, Yusuke Kurose, Tatsuya Harada, Ryuji Hamamoto

As a result, our SBMIR system enabled users to overcome previous challenges, including image retrieval based on fine-grained image characteristics, image retrieval without example images, and image retrieval for isolated samples.

Medical Image Retrieval Retrieval

Name Your Colour For the Task: Artificially Discover Colour Naming via Colour Quantisation Transformer

1 code implementation ICCV 2023 Shenghan Su, Lin Gu, Yue Yang, Zenghui Zhang, Tatsuya Harada

Besides, our colour quantisation method also offers an efficient quantisation method that effectively compresses the image storage while maintaining high performance in high-level recognition tasks such as classification and detection.

Improving Fairness in Image Classification via Sketching

1 code implementation31 Oct 2022 Ruichen Yao, Ziteng Cui, Xiaoxiao Li, Lin Gu

Fairness is a fundamental requirement for trustworthy and human-centered Artificial Intelligence (AI) system.

Classification Fairness +1

Memory Efficient Temporal & Visual Graph Model for Unsupervised Video Domain Adaptation

no code implementations13 Aug 2022 Xinyue Hu, Lin Gu, Liangchen Liu, Ruijiang Li, Chang Su, Tatsuya Harada, Yingying Zhu

Existing video domain adaption (DA) methods need to store all temporal combinations of video frames or pair the source and target videos, which are memory cost expensive and can't scale up to long videos.

Domain Adaptation Graph Attention

Exploring Resolution and Degradation Clues as Self-supervised Signal for Low Quality Object Detection

1 code implementation5 Aug 2022 Ziteng Cui, Yingying Zhu, Lin Gu, Guo-Jun Qi, Xiaoxiao Li, Renrui Zhang, Zenghui Zhang, Tatsuya Harada

Image restoration algorithms such as super resolution (SR) are indispensable pre-processing modules for object detection in low quality images.

Image Restoration Object +4

Surgical Skill Assessment via Video Semantic Aggregation

no code implementations4 Aug 2022 Zhenqiang Li, Lin Gu, Weimin WANG, Ryosuke Nakamura, Yoichi Sato

Automated video-based assessment of surgical skills is a promising task in assisting young surgical trainees, especially in poor-resource areas.

Representation Learning

You Only Need 90K Parameters to Adapt Light: A Light Weight Transformer for Image Enhancement and Exposure Correction

1 code implementation30 May 2022 Ziteng Cui, Kunchang Li, Lin Gu, Shenghan Su, Peng Gao, Zhengkai Jiang, Yu Qiao, Tatsuya Harada

Challenging illumination conditions (low-light, under-exposure and over-exposure) in the real world not only cast an unpleasant visual appearance but also taint the computer vision tasks.

Low-Light Image Enhancement object-detection +2

Multitask AET with Orthogonal Tangent Regularity for Dark Object Detection

2 code implementations ICCV 2021 Ziteng Cui, Guo-Jun Qi, Lin Gu, ShaoDi You, Zenghui Zhang, Tatsuya Harada

To enhance object detection in a dark environment, we propose a novel multitask auto encoding transformation (MAET) model which is able to explore the intrinsic pattern behind illumination translation.

Object object-detection +1

Revisiting Domain Generalized Stereo Matching Networks from a Feature Consistency Perspective

1 code implementation CVPR 2022 Jiawei Zhang, Xiang Wang, Xiao Bai, Chen Wang, Lei Huang, Yimin Chen, Lin Gu, Jun Zhou, Tatsuya Harada, Edwin R. Hancock

The stereo contrastive feature loss function explicitly constrains the consistency between learned features of matching pixel pairs which are observations of the same 3D points.

Contrastive Learning Stereo Matching

A Privacy-Preserving Unsupervised Domain Adaptation Framework for Clinical Text Analysis

no code implementations18 Jan 2022 Qiyuan An, Ruijiang Li, Lin Gu, Hao Zhang, Qingyu Chen, Zhiyong Lu, Fei Wang, Yingying Zhu

To evaluate our proposed method's utility and privacy loss, we apply our model on a medical report disease label classification task using two noisy challenging clinical text datasets.

Inference Attack Membership Inference Attack +4

RestoreDet: Degradation Equivariant Representation for Object Detection in Low Resolution Images

no code implementations7 Jan 2022 Ziteng Cui, Yingying Zhu, Lin Gu, Guo-Jun Qi, Xiaoxiao Li, Peng Gao, Zenghui Zhang, Tatsuya Harada

Image restoration algorithms such as super resolution (SR) are indispensable pre-processing modules for object detection in degraded images.

Image Restoration Object +4

Leveraging Human Selective Attention for Medical Image Analysis with Limited Training Data

no code implementations2 Dec 2021 Yifei HUANG, Xiaoxiao Li, Lijin Yang, Lin Gu, Yingying Zhu, Hirofumi Seo, Qiuming Meng, Tatsuya Harada, Yoichi Sato

Then we design a novel Auxiliary Attention Block (AAB) to allow information from SAN to be utilized by the backbone encoder to focus on selective areas.

Tumor Segmentation

Explainable Diabetic Retinopathy Detection and Retinal Image Generation

1 code implementation1 Jul 2021 Yuhao Niu, Lin Gu, Yitian Zhao, Feng Lu

Though deep learning has shown successful performance in classifying the label and severity stage of certain diseases, most of them give few explanations on how to make predictions.

Data Augmentation Diabetic Retinopathy Detection +4

Estimating and Improving Fairness with Adversarial Learning

1 code implementation7 Mar 2021 Xiaoxiao Li, Ziteng Cui, Yifan Wu, Lin Gu, Tatsuya Harada

To tackle this issue, we propose an adversarial multi-task training strategy to simultaneously mitigate and detect bias in the deep learning-based medical image analysis system.

Fairness

Goal-Oriented Gaze Estimation for Zero-Shot Learning

1 code implementation CVPR 2021 Yang Liu, Lei Zhou, Xiao Bai, Yifei HUANG, Lin Gu, Jun Zhou, Tatsuya Harada

Therefore, we introduce a novel goal-oriented gaze estimation module (GEM) to improve the discriminative attribute localization based on the class-level attributes for ZSL.

Attribute Gaze Estimation +1

Beyond Triplet Loss: Person Re-identification with Fine-grained Difference-aware Pairwise Loss

no code implementations22 Sep 2020 Cheng Yan, Guansong Pang, Xiao Bai, Jun Zhou, Lin Gu

The proposed loss is generic and can be used as a plugin to replace the triplet loss to significantly enhance different types of state-of-the-art approaches.

Person Re-Identification

Information Bottleneck Constrained Latent Bidirectional Embedding for Zero-Shot Learning

no code implementations16 Sep 2020 Yang Liu, Lei Zhou, Xiao Bai, Lin Gu, Tatsuya Harada, Jun Zhou

Though many ZSL methods rely on a direct mapping between the visual and the semantic space, the calibration deviation and hubness problem limit the generalization capability to unseen classes.

Attribute Zero-Shot Learning

Fixed Pattern Noise Reduction for Infrared Images Based on Cascade Residual Attention CNN

no code implementations22 Oct 2019 Juntao Guan, Rui Lai, Ai Xiong, Zesheng Liu, Lin Gu

Existing fixed pattern noise reduction (FPNR) methods are easily affected by the motion state of the scene and working condition of the image sensor, which leads to over smooth effects, ghosting artifacts as well as slow convergence rate.

Pathological Evidence Exploration in Deep Retinal Image Diagnosis

1 code implementation6 Dec 2018 Yuhao Niu, Lin Gu, Feng Lu, Feifan Lv, Zongji Wang, Imari Sato, Zijian Zhang, Yangyan Xiao, Xunzhang Dai, Tingting Cheng

Inspired by Koch's Postulates, a well-known strategy in medical research to identify the property of pathogen, we define a pathological descriptor that can be extracted from the activated neurons of a diabetic retinopathy detector.

Medical Diagnosis

ShelfNet for Fast Semantic Segmentation

6 code implementations27 Nov 2018 Juntang Zhuang, Junlin Yang, Lin Gu, Nicha Dvornek

Compared with real-time segmentation models such as BiSeNet, our model achieves higher accuracy at comparable speed on the Cityscapes Dataset, enabling the application in speed-demanding tasks such as street-scene understanding for autonomous driving.

Autonomous Driving Real-Time Semantic Segmentation +2

Deeply Learned Filter Response Functions for Hyperspectral Reconstruction

no code implementations CVPR 2018 Shijie Nie, Lin Gu, Yinqiang Zheng, Antony Lam, Nobutaka Ono, Imari Sato

More interestingly, by considering physical restrictions in the design process, we are able to realize the deeply learned spectral response functions by using modern film filter production technologies, and thus construct data-inspired multispectral cameras for snapshot hyperspectral imaging.

Spectral Reconstruction

From RGB to Spectrum for Natural Scenes via Manifold-Based Mapping

no code implementations ICCV 2017 Yan Jia, Yinqiang Zheng, Lin Gu, Art Subpa-Asa, Antony Lam, Yoichi Sato, Imari Sato

Spectral analysis of natural scenes can provide much more detailed information about the scene than an ordinary RGB camera.

Dimensionality Reduction

Virtual Blood Vessels in Complex Background using Stereo X-ray Images

no code implementations22 Sep 2017 Qiuyu Chen, Ryoma Bise, Lin Gu, Yinqiang Zheng, Imari Sato, Jenq-Neng Hwang, Nobuaki Imanishi, Sadakazu Aiso

We propose a fully automatic system to reconstruct and visualize 3D blood vessels in Augmented Reality (AR) system from stereo X-ray images with bones and body fat.

Stereo Matching Stereo Matching Hand

Learning to Boost Filamentary Structure Segmentation

no code implementations ICCV 2015 Lin Gu, Li Cheng

Step one of our approach centers on a data-driven latent classification tree model to detect the filamentary fragments.

Image Matting Segmentation

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