Search Results for author: Wenhan Yang

Found 48 papers, 17 papers with code

Cycle-Interactive Generative Adversarial Network for Robust Unsupervised Low-Light Enhancement

no code implementations3 Jul 2022 Zhangkai Ni, Wenhan Yang, Hanli Wang, Shiqi Wang, Lin Ma, Sam Kwong

Getting rid of the fundamental limitations in fitting to the paired training data, recent unsupervised low-light enhancement methods excel in adjusting illumination and contrast of images.

Low-Light Image Enhancement

Feature-Aligned Video Raindrop Removal with Temporal Constraints

no code implementations29 May 2022 Wending Yan, Lu Xu, Wenhan Yang, Robby T. Tan

Our single image module employs a raindrop removal network to generate initial raindrop removal results, and create a mask representing the differences between the input and initial output.

Optical Flow Estimation Rain Removal

UCL-Dehaze: Towards Real-world Image Dehazing via Unsupervised Contrastive Learning

1 code implementation4 May 2022 Yongzhen Wang, Xuefeng Yan, Fu Lee Wang, Haoran Xie, Wenhan Yang, Mingqiang Wei, Jing Qin

From a different yet new perspective, this paper explores contrastive learning with an adversarial training effort to leverage unpaired real-world hazy and clean images, thus bridging the gap between synthetic and real-world haze is avoided.

Contrastive Learning Image Dehazing

Towards Robust Rain Removal Against Adversarial Attacks: A Comprehensive Benchmark Analysis and Beyond

1 code implementation CVPR 2022 Yi Yu, Wenhan Yang, Yap-Peng Tan, Alex C. Kot

Finally, we examine various types of adversarial attacks that are specific to deraining problems and their effects on both human and machine vision tasks, including 1) rain region attacks, adding perturbations only in the rain regions to make the perturbations in the attacked rain images less visible; 2) object-sensitive attacks, adding perturbations only in regions near the given objects.

Benchmark Computer Vision +1

Neural Data-Dependent Transform for Learned Image Compression

no code implementations CVPR 2022 Dezhao Wang, Wenhan Yang, Yueyu Hu, Jiaying Liu

Learned image compression has achieved great success due to its excellent modeling capacity, but seldom further considers the Rate-Distortion Optimization (RDO) of each input image.

Image Compression

MSDN: Mutually Semantic Distillation Network for Zero-Shot Learning

1 code implementation CVPR 2022 Shiming Chen, Ziming Hong, Guo-Sen Xie, Wenhan Yang, Qinmu Peng, Kai Wang, Jian Zhao, Xinge You

Prior works either simply align the global features of an image with its associated class semantic vector or utilize unidirectional attention to learn the limited latent semantic representations, which could not effectively discover the intrinsic semantic knowledge e. g., attribute semantics) between visual and attribute features.

Transfer Learning Zero-Shot Learning

The Loop Game: Quality Assessment and Optimization for Low-Light Image Enhancement

no code implementations20 Feb 2022 Baoliang Chen, Lingyu Zhu, Hanwei Zhu, Wenhan Yang, Fangbo Lu, Shiqi Wang

In particular, we create a large-scale database for QUality assessment Of The Enhanced LOw-Light Image (QUOTE-LOL), which serves as the foundation in studying and developing objective quality assessment measures.

Low-Light Image Enhancement

Enhancing Low-Light Images in Real World via Cross-Image Disentanglement

no code implementations10 Jan 2022 Lanqing Guo, Renjie Wan, Wenhan Yang, Alex Kot, Bihan Wen

Images captured in the low-light condition suffer from low visibility and various imaging artifacts, e. g., real noise.

Disentanglement Low-Light Image Enhancement

URetinex-Net: Retinex-Based Deep Unfolding Network for Low-Light Image Enhancement

1 code implementation CVPR 2022 Wenhui Wu, Jian Weng, Pingping Zhang, Xu Wang, Wenhan Yang, Jianmin Jiang

Retinex model-based methods have shown to be effective in layer-wise manipulation with well-designed priors for low-light image enhancement.

Low-Light Image Enhancement

Towards Low Light Enhancement with RAW Images

no code implementations28 Dec 2021 Haofeng Huang, Wenhan Yang, Yueyu Hu, Jiaying Liu, Ling-Yu Duan

In this paper, we make the first benchmark effort to elaborate on the superiority of using RAW images in the low light enhancement and develop a novel alternative route to utilize RAW images in a more flexible and practical way.


Semantically Contrastive Learning for Low-light Image Enhancement

1 code implementation13 Dec 2021 Dong Liang, Ling Li, Mingqiang Wei, Shuo Yang, Liyan Zhang, Wenhan Yang, Yun Du, Huiyu Zhou

Low-light image enhancement (LLE) remains challenging due to the unfavorable prevailing low-contrast and weak-visibility problems of single RGB images.

Contrastive Learning Low-Light Image Enhancement +1

Video Coding for Machine: Compact Visual Representation Compression for Intelligent Collaborative Analytics

no code implementations18 Oct 2021 Wenhan Yang, Haofeng Huang, Yueyu Hu, Ling-Yu Duan, Jiaying Liu

By keeping in mind the transferability among different machine vision tasks (e. g. high-level semantic and mid-level geometry-related), we aim to support multiple tasks jointly at low bit rates.

Image Compression

Low-Light Image Enhancement with Normalizing Flow

1 code implementation13 Sep 2021 YuFei Wang, Renjie Wan, Wenhan Yang, Haoliang Li, Lap-Pui Chau, Alex C. Kot

To enhance low-light images to normally-exposed ones is highly ill-posed, namely that the mapping relationship between them is one-to-many.

Low-Light Image Enhancement

Self-Aligned Video Deraining With Transmission-Depth Consistency

1 code implementation CVPR 2021 Wending Yan, Robby T. Tan, Wenhan Yang, Dengxin Dai

In this paper, we address the problems of rain streaks and rain accumulation removal in video, by developing a self-aligned network with transmission-depth consistency.

Optical Flow Estimation Rain Removal

Revisit Visual Representation in Analytics Taxonomy: A Compression Perspective

no code implementations16 Jun 2021 Yueyu Hu, Wenhan Yang, Haofeng Huang, Jiaying Liu

Visual analytics have played an increasingly critical role in the Internet of Things, where massive visual signals have to be compressed and fed into machines.

Video Compression

HLA-Face: Joint High-Low Adaptation for Low Light Face Detection

1 code implementation CVPR 2021 Wenjing Wang, Wenhan Yang, Jiaying Liu

To reduce the burden of building new datasets for low light conditions, we make full use of existing normal light data and explore how to adapt face detectors from normal light to low light.

Autonomous Driving Face Detection

Camera Invariant Feature Learning for Generalized Face Anti-spoofing

no code implementations25 Jan 2021 Baoliang Chen, Wenhan Yang, Haoliang Li, Shiqi Wang, Sam Kwong

The first branch aims to learn the camera invariant spoofing features via feature level decomposition in the high frequency domain.

Face Anti-Spoofing

Towards Unsupervised Deep Image Enhancement with Generative Adversarial Network

1 code implementation30 Dec 2020 Zhangkai Ni, Wenhan Yang, Shiqi Wang, Lin Ma, Sam Kwong

In this paper, we present an unsupervised image enhancement generative adversarial network (UEGAN), which learns the corresponding image-to-image mapping from a set of images with desired characteristics in an unsupervised manner, rather than learning on a large number of paired images.

Image Enhancement L2 Regularization

Unpaired Image Enhancement with Quality-Attention Generative Adversarial Network

no code implementations30 Dec 2020 Zhangkai Ni, Wenhan Yang, Shiqi Wang, Lin Ma, Sam Kwong

The key novelty of the proposed QAGAN lies in the injected QAM for the generator such that it learns domain-relevant quality attention directly from the two domains.

Image Enhancement

Self-Learning Video Rain Streak Removal: When Cyclic Consistency Meets Temporal Correspondence

1 code implementation CVPR 2020 Wenhan Yang, Robby T. Tan, Shiqi Wang, Jiaying Liu

With this in mind, we construct a two-stage Self-Learned Deraining Network (SLDNet) to remove rain streaks based on both temporal correlation and consistency.

Motion Estimation Rain Removal +1

From Fidelity to Perceptual Quality: A Semi-Supervised Approach for Low-Light Image Enhancement

no code implementations CVPR 2020 Wenhan Yang, Shiqi Wang, Yuming Fang, Yue Wang, Jiaying Liu

A deep recursive band network (DRBN) is proposed to recover a linear band representation of an enhanced normal-light image with paired low/normal-light images, and then obtain an improved one by recomposing the given bands via another learnable linear transformation based on a perceptual quality-driven adversarial learning with unpaired data.

Low-Light Image Enhancement

Towards Analysis-friendly Face Representation with Scalable Feature and Texture Compression

no code implementations21 Apr 2020 Shurun Wang, Shiqi Wang, Wenhan Yang, Xinfeng Zhang, Shanshe Wang, Siwei Ma, Wen Gao

In particular, we study the feature and texture compression in a scalable coding framework, where the base layer serves as the deep learning feature and enhancement layer targets to perfectly reconstruct the texture.

Image Compression

End-to-End Facial Deep Learning Feature Compression with Teacher-Student Enhancement

no code implementations10 Feb 2020 Shurun Wang, Wenhan Yang, Shiqi Wang

In this paper, we propose a novel end-to-end feature compression scheme by leveraging the representation and learning capability of deep neural networks, towards intelligent front-end equipped analysis with promising accuracy and efficiency.

Learning End-to-End Lossy Image Compression: A Benchmark

2 code implementations10 Feb 2020 Yueyu Hu, Wenhan Yang, Zhan Ma, Jiaying Liu

In this paper, we first conduct a comprehensive literature survey of learned image compression methods.

Benchmark Image Compression

Combining Progressive Rethinking and Collaborative Learning: A Deep Framework for In-Loop Filtering

no code implementations16 Jan 2020 Dezhao Wang, Sifeng Xia, Wenhan Yang, Jiaying Liu

For (2), we extract both intra-frame and inter-frame side information for better context modeling.

Video Coding for Machines: A Paradigm of Collaborative Compression and Intelligent Analytics

no code implementations10 Jan 2020 Ling-Yu Duan, Jiaying Liu, Wenhan Yang, Tiejun Huang, Wen Gao

Meanwhile, we systematically review state-of-the-art techniques in video compression and feature compression from the unique perspective of MPEG standardization, which provides the academic and industrial evidence to realize the collaborative compression of video and feature streams in a broad range of AI applications.

Video Compression

Towards Coding for Human and Machine Vision: A Scalable Image Coding Approach

no code implementations9 Jan 2020 Yueyu Hu, Shuai Yang, Wenhan Yang, Ling-Yu Duan, Jiaying Liu

In this paper, we come up with a novel image coding framework by leveraging both the compressive and the generative models, to support machine vision and human perception tasks jointly.

Facial Landmark Detection Image Reconstruction

An Emerging Coding Paradigm VCM: A Scalable Coding Approach Beyond Feature and Signal

no code implementations9 Jan 2020 Sifeng Xia, Kunchangtai Liang, Wenhan Yang, Ling-Yu Duan, Jiaying Liu

To this end, we make endeavors in leveraging the strength of predictive and generative models to support advanced compression techniques for both machine and human vision tasks simultaneously, in which visual features serve as a bridge to connect signal-level and task-level compact representations in a scalable manner.

Action Recognition SSIM

Single Image Deraining: From Model-Based to Data-Driven and Beyond

no code implementations16 Dec 2019 Wenhan Yang, Robby T. Tan, Shiqi Wang, Yuming Fang, Jiaying Liu

The goal of single-image deraining is to restore the rain-free background scenes of an image degraded by rain streaks and rain accumulation.

Single Image Deraining

A Comprehensive Benchmark for Single Image Compression Artifacts Reduction

no code implementations9 Sep 2019 Jiaying Liu, Dong Liu, Wenhan Yang, Sifeng Xia, Xiaoshuai Zhang, Yuanying Dai

We present a comprehensive study and evaluation of existing single image compression artifacts removal algorithms, using a new 4K resolution benchmark including diversified foreground objects and background scenes with rich structures, called Large-scale Ideal Ultra high definition 4K (LIU4K) benchmark.

Benchmark Image Compression +1

Frame-Consistent Recurrent Video Deraining With Dual-Level Flow

1 code implementation CVPR 2019 Wenhan Yang, Jiaying Liu, Jiashi Feng

The proposed framework is built upon a two-stage recurrent network with dual-level flow regularizations to perform the inverse recovery process of the rain synthesis model for video deraining.

Rain Removal

Deep Reference Generation with Multi-Domain Hierarchical Constraints for Inter Prediction

no code implementations16 May 2019 Jiaying Liu, Sifeng Xia, Wenhan Yang

In this paper, we address the problem by proposing a deep frame interpolation network to generate additional reference frames in coding scenarios.

UG$^{2+}$ Track 2: A Collective Benchmark Effort for Evaluating and Advancing Image Understanding in Poor Visibility Environments

no code implementations9 Apr 2019 Ye Yuan, Wenhan Yang, Wenqi Ren, Jiaying Liu, Walter J. Scheirer, Zhangyang Wang

The UG$^{2+}$ challenge in IEEE CVPR 2019 aims to evoke a comprehensive discussion and exploration about how low-level vision techniques can benefit the high-level automatic visual recognition in various scenarios.

Benchmark Face Detection

Context-Aware Text-Based Binary Image Stylization and Synthesis

no code implementations9 Oct 2018 Shuai Yang, Jiaying Liu, Wenhan Yang, Zongming Guo

The stylization is then followed by a context-aware layout design algorithm, where cues for both seamlessness and aesthetics are employed to determine the optimal layout of the shape in the background.

Image Inpainting Image Stylization +1

Deep Retinex Decomposition for Low-Light Enhancement

2 code implementations14 Aug 2018 Chen Wei, Wenjing Wang, Wenhan Yang, Jiaying Liu

Based on the decomposition, subsequent lightness enhancement is conducted on illumination by an enhancement network called Enhance-Net, and for joint denoising there is a denoising operation on reflectance.

Denoising Low-Light Image Enhancement

Progressive Spatial Recurrent Neural Network for Intra Prediction

2 code implementations6 Jul 2018 Yueyu Hu, Wenhan Yang, Mading Li, Jiaying Liu

With preceding pixels as the context, traditional intra prediction schemes generate linear predictions based on several predefined directions (i. e. modes) for blocks to be encoded.

A Group Variational Transformation Neural Network for Fractional Interpolation of Video Coding

no code implementations19 Jun 2018 Sifeng Xia, Wenhan Yang, Yueyu Hu, Siwei Ma, Jiaying Liu

Then a group variational transformation technique is used to transform a group of copied shared feature maps to samples at different sub-pixel positions.


Attentive Generative Adversarial Network for Raindrop Removal from a Single Image

3 code implementations CVPR 2018 Rui Qian, Robby T. Tan, Wenhan Yang, Jiajun Su, Jiaying Liu

This injection of visual attention to both generative and discriminative networks is the main contribution of this paper.

Rain Removal

Dual Recovery Network with Online Compensation for Image Super-Resolution

no code implementations20 Jan 2017 Sifeng Xia, Wenhan Yang, Jiaying Liu, Zongming Guo

In particular, we infer the HF information based on both the LR image and similar HR references which are retrieved online.

Image Super-Resolution

Robust LSTM-Autoencoders for Face De-Occlusion in the Wild

no code implementations27 Dec 2016 Fang Zhao, Jiashi Feng, Jian Zhao, Wenhan Yang, Shuicheng Yan

The first one, named multi-scale spatial LSTM encoder, reads facial patches of various scales sequentially to output a latent representation, and occlusion-robustness is achieved owing to the fact that the influence of occlusion is only upon some of the patches.

Face Recognition

Deep Joint Rain Detection and Removal from a Single Image

2 code implementations CVPR 2017 Wenhan Yang, Robby T. Tan, Jiashi Feng, Jiaying Liu, Zongming Guo, Shuicheng Yan

Based on the first model, we develop a multi-task deep learning architecture that learns the binary rain streak map, the appearance of rain streaks, and the clean background, which is our ultimate output.

Rain Removal

Photo Stylistic Brush: Robust Style Transfer via Superpixel-Based Bipartite Graph

no code implementations13 Jun 2016 Jiaying Liu, Wenhan Yang, Xiaoyan Sun, Wen-Jun Zeng

With the rapid development of social network and multimedia technology, customized image and video stylization has been widely used for various social-media applications.

Style Transfer Superpixels

Deep Edge Guided Recurrent Residual Learning for Image Super-Resolution

no code implementations29 Apr 2016 Wenhan Yang, Jiashi Feng, Jianchao Yang, Fang Zhao, Jiaying Liu, Zongming Guo, Shuicheng Yan

To address this essentially ill-posed problem, we introduce a Deep Edge Guided REcurrent rEsidual~(DEGREE) network to progressively recover the high-frequency details.

Image Super-Resolution

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