Search Results for author: Chia-Wen Lin

Found 38 papers, 15 papers with code

HardGAN: A Haze-Aware Representation Distillation GAN for Single Image Dehazing

no code implementations ECCV 2020 Qili Deng, Ziling Huang, Chung-Chi Tsai, Chia-Wen Lin

In this paper, we present a Haze-Aware Representation Distillation Generative Adversarial Network named HardGAN for single-image dehazing.

Image Dehazing Single Image Dehazing +1

Physics-guided Terahertz Computational Imaging

no code implementations30 Apr 2022 Weng-Tai Su, Yi-Chun Hung, Po-Jen Yu, Chia-Wen Lin, Shang-Hua Yang

Visualizing information inside objects is an ever-lasting need to bridge the world from physics, chemistry, biology to computation.

Image Restoration

Stripformer: Strip Transformer for Fast Image Deblurring

no code implementations10 Apr 2022 Fu-Jen Tsai, Yan-Tsung Peng, Yen-Yu Lin, Chung-Chi Tsai, Chia-Wen Lin

Images taken in dynamic scenes may contain unwanted motion blur, which significantly degrades visual quality.

Deblurring Image Deblurring

Pruning Networks with Cross-Layer Ranking & k-Reciprocal Nearest Filters

1 code implementation15 Feb 2022 Mingbao Lin, Liujuan Cao, Yuxin Zhang, Ling Shao, Chia-Wen Lin, Rongrong Ji

Then, we introduce a recommendation-based filter selection scheme where each filter recommends a group of its closest filters.

Image Classification Network Pruning

Keeping Deep Lithography Simulators Updated: Global-Local Shape-Based Novelty Detection and Active Learning

no code implementations24 Jan 2022 Hao-Chiang Shao, Hsing-Lei Ping, Kuo-shiuan Chen, Weng-Tai Su, Chia-Wen Lin, Shao-Yun Fang, Pin-Yian Tsai, Yan-Hsiu Liu

To address the problem, we propose a deep learning-based layout novelty detection scheme to identify novel (unseen) layout patterns, which cannot be well predicted by a pre-trained pre-simulation model.

Active Learning

Both Style and Fog Matter: Cumulative Domain Adaptation for Semantic Foggy Scene Understanding

no code implementations1 Dec 2021 Xianzheng Ma, Zhixiang Wang, Yacheng Zhan, Yinqiang Zheng, Zheng Wang, Dengxin Dai, Chia-Wen Lin

Unlike previous methods that mainly focus on closing the domain gap caused by fog -- defogging the foggy images or fogging the clear images, we propose to alleviate the domain gap by considering fog influence and style variation simultaneously.

Disentanglement Domain Adaptation +1

Fast Graph Sampling for Short Video Summarization using Gershgorin Disc Alignment

no code implementations21 Oct 2021 Sadid Sahami, Gene Cheung, Chia-Wen Lin

We prove that, after partitioning $\mathcal{G}$ into $Q$ sub-graphs $\{\mathcal{G}^q\}^Q_{q=1}$, the smallest Gershgorin circle theorem (GCT) lower bound of $Q$ corresponding coefficient matrices -- $\min_q \lambda^-_{\min}(\mathbf{B}^q)$ -- is a lower bound for $\lambda_{\min}(\mathbf{B})$.

Graph Sampling Video Summarization

Discover Cross-Modality Nuances for Visible-Infrared Person Re-Identification

no code implementations CVPR 2021 Qiong Wu, Pingyang Dai, Jie Chen, Chia-Wen Lin, Yongjian Wu, Feiyue Huang, Bineng Zhong, Rongrong Ji

In this paper, we propose a joint Modality and Pattern Alignment Network (MPANet) to discover cross-modality nuances in different patterns for visible-infrared person Re-ID, which introduces a modality alleviation module and a pattern alignment module to jointly extract discriminative features.

Person Re-Identification

Carrying out CNN Channel Pruning in a White Box

1 code implementation24 Apr 2021 Yuxin Zhang, Mingbao Lin, Chia-Wen Lin, Jie Chen, Feiyue Huang, Yongjian Wu, Yonghong Tian, Rongrong Ji

Specifically, to model the contribution of each channel to differentiating categories, we develop a class-wise mask for each channel, implemented in a dynamic training manner w. r. t.

Image Classification

Asymmetric CNN for image super-resolution

1 code implementation25 Mar 2021 Chunwei Tian, Yong Xu, WangMeng Zuo, Chia-Wen Lin, David Zhang

In this paper, we propose an asymmetric CNN (ACNet) comprising an asymmetric block (AB), a memory enhancement block (MEB) and a high-frequency feature enhancement block (HFFEB) for image super-resolution.

Image Super-Resolution

Degrade is Upgrade: Learning Degradation for Low-light Image Enhancement

1 code implementation19 Mar 2021 Kui Jiang, Zhongyuan Wang, Zheng Wang, Chen Chen, Peng Yi, Tao Lu, Chia-Wen Lin

Different from existing methods tending to accomplish the relighting task directly by ignoring the fidelity and naturalness recovery, we investigate the intrinsic degradation and relight the low-light image while refining the details and color in two steps.

Low-Light Image Enhancement

Ensemble Learning with Manifold-Based Data Splitting for Noisy Label Correction

no code implementations13 Mar 2021 Hao-Chiang Shao, Hsin-Chieh Wang, Weng-Tai Su, Chia-Wen Lin

Here we focus on the problem that noisy labels are primarily mislabeled samples, which tend to be concentrated near decision boundaries, rather than uniformly distributed, and whose features should be equivocal.

Ensemble Learning

AniGAN: Style-Guided Generative Adversarial Networks for Unsupervised Anime Face Generation

3 code implementations24 Feb 2021 Bing Li, Yuanlue Zhu, Yitong Wang, Chia-Wen Lin, Bernard Ghanem, Linlin Shen

Specifically, a new generator architecture is proposed to simultaneously transfer color/texture styles and transform local facial shapes into anime-like counterparts based on the style of a reference anime-face, while preserving the global structure of the source photo-face.

Face Generation Translation

SiMaN: Sign-to-Magnitude Network Binarization

1 code implementation16 Feb 2021 Mingbao Lin, Rongrong Ji, Zihan Xu, Baochang Zhang, Fei Chao, Mingliang Xu, Chia-Wen Lin, Ling Shao

In this paper, we show that our weight binarization provides an analytical solution by encoding high-magnitude weights into +1s, and 0s otherwise.

Binarization

Dual-Level Collaborative Transformer for Image Captioning

1 code implementation16 Jan 2021 Yunpeng Luo, Jiayi Ji, Xiaoshuai Sun, Liujuan Cao, Yongjian Wu, Feiyue Huang, Chia-Wen Lin, Rongrong Ji

Descriptive region features extracted by object detection networks have played an important role in the recent advancements of image captioning.

Image Captioning Object Detection

High Quality Disparity Remapping With Two-Stage Warping

no code implementations ICCV 2021 Bing Li, Chia-Wen Lin, Cheng Zheng, Shan Liu, Junsong Yuan, Bernard Ghanem, C.-C. Jay Kuo

In the second stage, we derive another warping model to refine warping results in less important regions by eliminating serious distortions in shape, disparity and 3D structure.

Image Inpainting Guided by Coherence Priors of Semantics and Textures

no code implementations CVPR 2021 Liang Liao, Jing Xiao, Zheng Wang, Chia-Wen Lin, Shin'ichi Satoh

In this paper, we introduce coherence priors between the semantics and textures which make it possible to concentrate on completing separate textures in a semantic-wise manner.

Image Inpainting Semantic Segmentation

Forgery Blind Inspection for Detecting Manipulations of Gel Electrophoresis Images

1 code implementation28 Oct 2020 Hao-Chiang Shao, Ya-Jen Cheng, Meng-Yun Duh, Chia-Wen Lin

Recently, falsified images have been found in papers involved in research misconducts.

Rotated Binary Neural Network

2 code implementations NeurIPS 2020 Mingbao Lin, Rongrong Ji, Zihan Xu, Baochang Zhang, Yan Wang, Yongjian Wu, Feiyue Huang, Chia-Wen Lin

In this paper, for the first time, we explore the influence of angular bias on the quantization error and then introduce a Rotated Binary Neural Network (RBNN), which considers the angle alignment between the full-precision weight vector and its binarized version.

Binarization Quantization

Graph Signal Processing for Geometric Data and Beyond: Theory and Applications

no code implementations5 Aug 2020 Wei Hu, Jiahao Pang, Xian-Ming Liu, Dong Tian, Chia-Wen Lin, Anthony Vetro

Geometric data acquired from real-world scenes, e. g., 2D depth images, 3D point clouds, and 4D dynamic point clouds, have found a wide range of applications including immersive telepresence, autonomous driving, surveillance, etc.

Autonomous Driving

Lightweight image super-resolution with enhanced CNN

1 code implementation8 Jul 2020 Chunwei Tian, Ruibin Zhuge, Zhihao Wu, Yong Xu, WangMeng Zuo, Chen Chen, Chia-Wen Lin

Finally, the IRB uses coarse high-frequency features from the RB to learn more accurate SR features and construct a SR image.

Image Super-Resolution

Designing and Training of A Dual CNN for Image Denoising

1 code implementation8 Jul 2020 Chunwei Tian, Yong Xu, WangMeng Zuo, Bo Du, Chia-Wen Lin, David Zhang

The enhancement block gathers and fuses the global and local features to provide complementary information for the latter network.

Image Denoising

DotFAN: A Domain-transferred Face Augmentation Network for Pose and Illumination Invariant Face Recognition

no code implementations23 Feb 2020 Hao-Chiang Shao, Kang-Yu Liu, Chia-Wen Lin, Jiwen Lu

With their aid, DotFAN can learn a disentangled face representation and effectively generate face images of various facial attributes while preserving the identity of augmented faces.

Face Recognition

From IC Layout to Die Photo: A CNN-Based Data-Driven Approach

no code implementations11 Feb 2020 Hao-Chiang Shao, Chao-Yi Peng, Jun-Rei Wu, Chia-Wen Lin, Shao-Yun Fang, Pin-Yen Tsai, Yan-Hsiu Liu

By learning the shape correspondences between pairs of layout design patterns and their scanning electron microscope (SEM) images of the product wafer thereof, given an IC layout pattern, LithoNet can mimic the fabrication process to predict its fabricated circuit shape.

Deep Learning on Image Denoising: An overview

no code implementations31 Dec 2019 Chunwei Tian, Lunke Fei, Wenxian Zheng, Yong Xu, WangMeng Zuo, Chia-Wen Lin

However, there are substantial differences in the various types of deep learning methods dealing with image denoising.

Image Denoising

A Real-time Global Inference Network for One-stage Referring Expression Comprehension

1 code implementation7 Dec 2019 Yiyi Zhou, Rongrong Ji, Gen Luo, Xiaoshuai Sun, Jinsong Su, Xinghao Ding, Chia-Wen Lin, Qi Tian

Referring Expression Comprehension (REC) is an emerging research spot in computer vision, which refers to detecting the target region in an image given an text description.

Referring Expression Referring Expression Comprehension

Semantic-aware Image Deblurring

no code implementations9 Oct 2019 Fuhai Chen, Rongrong Ji, Chengpeng Dai, Xiaoshuai Sun, Chia-Wen Lin, Jiayi Ji, Baochang Zhang, Feiyue Huang, Liujuan Cao

Specially, we propose a novel Structured-Spatial Semantic Embedding model for image deblurring (termed S3E-Deblur), which introduces a novel Structured-Spatial Semantic tree model (S3-tree) to bridge two basic tasks in computer vision: image deblurring (ImD) and image captioning (ImC).

Deblurring Image Captioning +1

DotSCN: Group Re-identification via Domain-Transferred Single and Couple Representation Learning

no code implementations13 May 2019 Ziling Huang, Zheng Wang, Chung-Chi Tsai, Shin'ichi Satoh, Chia-Wen Lin

To gain the superiority of deep learning models, we treat a group as multiple persons and transfer the domain of a labeled ReID dataset to a G-ReID target dataset style to learn single representations.

Person Re-Identification Representation Learning

How to Write High-quality News on Social Network? Predicting News Quality by Mining Writing Style

no code implementations2 Feb 2019 Yuting Yang, Juan Cao, Mingyan Lu, Jintao Li, Chia-Wen Lin

SNQAM performs excellently on predicting quality, presenting interpretable quality score and giving accessible suggestions on how to improve it according to writing guidelines we referred to.

SiGAN: Siamese Generative Adversarial Network for Identity-Preserving Face Hallucination

1 code implementation22 Jul 2018 Chih-Chung Hsu, Chia-Wen Lin, Weng-Tai Su, Gene Cheung

Despite generative adversarial networks (GANs) can hallucinate photo-realistic high-resolution (HR) faces from low-resolution (LR) faces, they cannot guarantee preserving the identities of hallucinated HR faces, making the HR faces poorly recognizable.

Face Hallucination Face Reconstruction +1

Depth-Aware Stereo Video Retargeting

no code implementations CVPR 2018 Bing Li, Chia-Wen Lin, Boxin Shi, Tiejun Huang, Wen Gao, C. -C. Jay Kuo

As compared with traditional video retargeting, stereo video retargeting poses new challenges because stereo video contains the depth information of salient objects and its time dynamics.

CNN-Based Joint Clustering and Representation Learning with Feature Drift Compensation for Large-Scale Image Data

no code implementations19 May 2017 Chih-Chung Hsu, Chia-Wen Lin

Given a large unlabeled set of images, how to efficiently and effectively group them into clusters based on extracted visual representations remains a challenging problem.

Representation Learning

Graph Fourier Transform with Negative Edges for Depth Image Coding

no code implementations10 Feb 2017 Weng-Tai Su, Gene Cheung, Chia-Wen Lin

Recent advent in graph signal processing (GSP) has led to the development of new graph-based transforms and wavelets for image / video coding, where the underlying graph describes inter-pixel correlations.

Robust Semi-Supervised Graph Classifier Learning with Negative Edge Weights

no code implementations15 Nov 2016 Gene Cheung, Weng-Tai Su, Yu Mao, Chia-Wen Lin

In response, we derive an optimal perturbation matrix $\boldsymbol{\Delta}$ - based on a fast lower-bound computation of the minimum eigenvalue of $\mathbf{L}$ via a novel application of the Haynsworth inertia additivity formula---so that $\mathbf{L} + \boldsymbol{\Delta}$ is positive semi-definite, resulting in a stable signal prior.

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