Search Results for author: Xiaojie Guo

Found 51 papers, 28 papers with code

NTIRE 2024 Challenge on Low Light Image Enhancement: Methods and Results

3 code implementations22 Apr 2024 Xiaoning Liu, Zongwei Wu, Ao Li, Florin-Alexandru Vasluianu, Yulun Zhang, Shuhang Gu, Le Zhang, Ce Zhu, Radu Timofte, Zhi Jin, Hongjun Wu, Chenxi Wang, Haitao Ling, Yuanhao Cai, Hao Bian, Yuxin Zheng, Jing Lin, Alan Yuille, Ben Shao, Jin Guo, Tianli Liu, Mohao Wu, Yixu Feng, Shuo Hou, Haotian Lin, Yu Zhu, Peng Wu, Wei Dong, Jinqiu Sun, Yanning Zhang, Qingsen Yan, Wenbin Zou, Weipeng Yang, Yunxiang Li, Qiaomu Wei, Tian Ye, Sixiang Chen, Zhao Zhang, Suiyi Zhao, Bo wang, Yan Luo, Zhichao Zuo, Mingshen Wang, Junhu Wang, Yanyan Wei, Xiaopeng Sun, Yu Gao, Jiancheng Huang, Hongming Chen, Xiang Chen, Hui Tang, Yuanbin Chen, Yuanbo Zhou, Xinwei Dai, Xintao Qiu, Wei Deng, Qinquan Gao, Tong Tong, Mingjia Li, Jin Hu, Xinyu He, Xiaojie Guo, sabarinathan, K Uma, A Sasithradevi, B Sathya Bama, S. Mohamed Mansoor Roomi, V. Srivatsav, Jinjuan Wang, Long Sun, Qiuying Chen, Jiahong Shao, Yizhi Zhang, Marcos V. Conde, Daniel Feijoo, Juan C. Benito, Alvaro García, Jaeho Lee, Seongwan Kim, Sharif S M A, Nodirkhuja Khujaev, Roman Tsoy, Ali Murtaza, Uswah Khairuddin, Ahmad 'Athif Mohd Faudzi, Sampada Malagi, Amogh Joshi, Nikhil Akalwadi, Chaitra Desai, Ramesh Ashok Tabib, Uma Mudenagudi, Wenyi Lian, Wenjing Lian, Jagadeesh Kalyanshetti, Vijayalaxmi Ashok Aralikatti, Palani Yashaswini, Nitish Upasi, Dikshit Hegde, Ujwala Patil, Sujata C, Xingzhuo Yan, Wei Hao, Minghan Fu, Pooja Choksy, Anjali Sarvaiya, Kishor Upla, Kiran Raja, Hailong Yan, Yunkai Zhang, Baiang Li, Jingyi Zhang, Huan Zheng

This paper reviews the NTIRE 2024 low light image enhancement challenge, highlighting the proposed solutions and results.

4k Low-Light Image Enhancement +1

TSTTC: A Large-Scale Dataset for Time-to-Contact Estimation in Driving Scenarios

1 code implementation4 Sep 2023 Yuheng Shi, Zehao Huang, Yan Yan, Naiyan Wang, Xiaojie Guo

Time-to-Contact (TTC) estimation is a critical task for assessing collision risk and is widely used in various driver assistance and autonomous driving systems.

Autonomous Driving Neural Rendering

Practical Edge Detection via Robust Collaborative Learning

1 code implementation27 Aug 2023 Yuanbin Fu, Xiaojie Guo

Edge detection, as a core component in a wide range of visionoriented tasks, is to identify object boundaries and prominent edges in natural images.

Edge Detection

Single Image Reflection Separation via Component Synergy

1 code implementation ICCV 2023 Qiming Hu, Xiaojie Guo

The reflection superposition phenomenon is complex and widely distributed in the real world, which derives various simplified linear and nonlinear formulations of the problem.

Reflection Removal

Adaptive Vague Preference Policy Learning for Multi-round Conversational Recommendation

no code implementations7 Jun 2023 Gangyi Zhang, Chongming Gao, Wenqiang Lei, Xiaojie Guo, Shijun Li, Hongshen Chen, Zhuozhi Ding, Sulong Xu, Lingfei Wu

In the VPMCR setting, we propose a solution called Adaptive Vague Preference Policy Learning (AVPPL), which consists of two components: Ambiguity-aware Soft Estimation (ASE) and Dynamism-aware Policy Learning (DPL).

Decision Making Recommendation Systems

Adaptive Texture Filtering for Single-Domain Generalized Segmentation

1 code implementation6 Mar 2023 Xinhui Li, Mingjia Li, Yaxing Wang, Chuan-Xian Ren, Xiaojie Guo

Domain generalization in semantic segmentation aims to alleviate the performance degradation on unseen domains through learning domain-invariant features.

Domain Generalization Semantic Segmentation

Face Inverse Rendering via Hierarchical Decoupling

1 code implementation17 Jan 2023 Meng Wang, Xiaojie Guo, Wenjing Dai, Jiawan Zhang

Previous face inverse rendering methods often require synthetic data with ground truth and/or professional equipment like a lighting stage.

Inverse Rendering

Pruning Before Training May Improve Generalization, Provably

no code implementations1 Jan 2023 Hongru Yang, Yingbin Liang, Xiaojie Guo, Lingfei Wu, Zhangyang Wang

It is shown that as long as the pruning fraction is below a certain threshold, gradient descent can drive the training loss toward zero and the network exhibits good generalization performance.

Network Pruning

Multi-objective Deep Data Generation with Correlated Property Control

no code implementations1 Oct 2022 Shiyu Wang, Xiaojie Guo, Xuanyang Lin, Bo Pan, Yuanqi Du, Yinkai Wang, Yanfang Ye, Ashley Ann Petersen, Austin Leitgeb, Saleh AlKhalifa, Kevin Minbiole, William Wuest, Amarda Shehu, Liang Zhao

Developing deep generative models has been an emerging field due to the ability to model and generate complex data for various purposes, such as image synthesis and molecular design.

Image Generation

YOLOV: Making Still Image Object Detectors Great at Video Object Detection

1 code implementation20 Aug 2022 Yuheng Shi, Naiyan Wang, Xiaojie Guo

On the positive side, the detection in a certain frame of a video, compared with that in a still image, can draw support from other frames.

Object object-detection +1

Controllable Data Generation by Deep Learning: A Review

no code implementations19 Jul 2022 Shiyu Wang, Yuanqi Du, Xiaojie Guo, Bo Pan, Zhaohui Qin, Liang Zhao

This article is a systematic review that explains this promising research area, commonly known as controllable deep data generation.

Speech Synthesis

Automatic Controllable Product Copywriting for E-Commerce

1 code implementation21 Jun 2022 Xiaojie Guo, Qingkai Zeng, Meng Jiang, Yun Xiao, Bo Long, Lingfei Wu

Automatic product description generation for e-commerce has witnessed significant advancement in the past decade.

Aspect Extraction Language Modelling +2

Interpretable Molecular Graph Generation via Monotonic Constraints

no code implementations28 Feb 2022 Yuanqi Du, Xiaojie Guo, Amarda Shehu, Liang Zhao

Recent advances in deep graph generative models treat molecule design as graph generation problems which provide new opportunities toward the breakthrough of this long-lasting problem.

Disentanglement Drug Discovery +2

Disentangled Spatiotemporal Graph Generative Models

no code implementations28 Feb 2022 Yuanqi Du, Xiaojie Guo, Hengning Cao, Yanfang Ye, Liang Zhao

Spatiotemporal graph represents a crucial data structure where the nodes and edges are embedded in a geometric space and can evolve dynamically over time.

Disentanglement Graph Generation +1

Deep Generative Model for Periodic Graphs

1 code implementation28 Jan 2022 Shiyu Wang, Xiaojie Guo, Liang Zhao

To address them, this paper proposes Periodical-Graph Disentangled Variational Auto-encoder (PGD-VAE), a new deep generative models for periodic graphs that can automatically learn, disentangle, and generate local and global graph patterns.


Compact Graph Structure Learning via Mutual Information Compression

2 code implementations14 Jan 2022 Nian Liu, Xiao Wang, Lingfei Wu, Yu Chen, Xiaojie Guo, Chuan Shi

Furthermore, we maintain the performance of estimated views and the final view and reduce the mutual information of every two views.

Graph structure learning

Self-Augmented Unpaired Image Dehazing via Density and Depth Decomposition

1 code implementation CVPR 2022 Yang Yang, Chaoyue Wang, Risheng Liu, Lin Zhang, Xiaojie Guo, DaCheng Tao

With estimated scene depth, our method is capable of re-rendering hazy images with different thicknesses which further benefits the training of the dehazing network.

Image Dehazing

Low-light Image Enhancement via Breaking Down the Darkness

1 code implementation30 Nov 2021 Qiming Hu, Xiaojie Guo

Assuming that an image can be decomposed into texture (with possible noise) and color components, one can specifically execute noise removal and color correction along with light adjustment.

Low-Light Image Enhancement

Trash or Treasure? An Interactive Dual-Stream Strategy for Single Image Reflection Separation

1 code implementation NeurIPS 2021 Qiming Hu, Xiaojie Guo

Single image reflection separation (SIRS), as a representative blind source separation task, aims to recover two layers, $\textit{i. e.}$, transmission and reflection, from one mixed observation, which is challenging due to the highly ill-posed nature.

blind source separation Reflection Removal

Boosting Semantic Segmentation via Feature Enhancement

no code implementations29 Sep 2021 Liu Zhi, Xiaojie Guo, Zhang Yi

Semantic segmentation aims to map each pixel of an image into its correspond-ing semantic label.

Segmentation Semantic Segmentation

GraphGT: Machine Learning Datasets for Graph Generation and Transformation

1 code implementation NeurIPS Workshop AI4Scien 2021 Yuanqi Du, Shiyu Wang, Xiaojie Guo, Hengning Cao, Shujie Hu, Junji Jiang, Aishwarya Varala, Abhinav Angirekula, Liang Zhao

Graph generation, which learns from known graphs and discovers novel graphs, has great potential in numerous research topics like drug design and mobility synthesis and is one of the fastest-growing domains recently due to its promise for discovering new knowledge.

BIG-bench Machine Learning Graph Generation +1

Graph Neural Networks for Natural Language Processing: A Survey

1 code implementation10 Jun 2021 Lingfei Wu, Yu Chen, Kai Shen, Xiaojie Guo, Hanning Gao, Shucheng Li, Jian Pei, Bo Long

Deep learning has become the dominant approach in coping with various tasks in Natural LanguageProcessing (NLP).

Decoder graph construction +1

Bilateral attention decoder: A lightweight decoder for real-time semantic segmentation

no code implementations30 Jan 2021 Chengli Peng, Jiayi Ma, Chen Chen, Xiaojie Guo

To verify the efficiency of the proposed bilateral attention decoder, we adopt a lightweight network as the backbone and compare our proposed method with other state-of-the-art real-time semantic segmentation methods on the Cityscapes and Camvid datasets.

Decoder Real-Time Semantic Segmentation +1

Property Controllable Variational Autoencoder via Invertible Mutual Dependence

1 code implementation ICLR 2021 Xiaojie Guo, Yuanqi Du, Liang Zhao

Deep generative models have made important progress towards modeling complex, high dimensional data via learning latent representations.


A Systematic Survey on Deep Generative Models for Graph Generation

no code implementations13 Jul 2020 Xiaojie Guo, Liang Zhao

Graphs are important data representations for describing objects and their relationships, which appear in a wide diversity of real-world scenarios.

Graph Generation

Interpretable Deep Graph Generation with Node-Edge Co-Disentanglement

1 code implementation9 Jun 2020 Xiaojie Guo, Liang Zhao, Zhao Qin, Lingfei Wu, Amarda Shehu, Yanfang Ye

Disentangled representation learning has recently attracted a significant amount of attention, particularly in the field of image representation learning.

Disentanglement Graph Generation

Generating Tertiary Protein Structures via an Interpretative Variational Autoencoder

1 code implementation8 Apr 2020 Xiaojie Guo, Yuanqi Du, Sivani Tadepalli, Liang Zhao, Amarda Shehu

Much scientific enquiry across disciplines is founded upon a mechanistic treatment of dynamic systems that ties form to function.

Protein Structure Prediction Stochastic Optimization

Deep Multi-attributed Graph Translation with Node-Edge Co-evolution

1 code implementation22 Mar 2020 Xiaojie Guo, Liang Zhao, Cameron Nowzari, Setareh Rafatirad, Houman Homayoun, Sai Manoj Pudukotai Dinakarrao

Then, a spectral graph regularization based on our non-parametric graph Laplacian is proposed in order to learn and maintain the consistency of the predicted nodes and edges.


LaFIn: Generative Landmark Guided Face Inpainting

1 code implementation26 Nov 2019 Yang Yang, Xiaojie Guo, Jiayi Ma, Lin Ma, Haibin Ling

It is challenging to inpaint face images in the wild, due to the large variation of appearance, such as different poses, expressions and occlusions.

Attribute Facial Inpainting

EDIT: Exemplar-Domain Aware Image-to-Image Translation

1 code implementation24 Nov 2019 Yuanbin Fu, Jiayi Ma, Lin Ma, Xiaojie Guo

The principle behind is that, for images from multiple domains, the content features can be obtained by a uniform extractor, while (re-)stylization is achieved by mapping the extracted features specifically to different purposes (domains and exemplars).

Generative Adversarial Network Image-to-Image Translation +1


no code implementations25 Sep 2019 Liang Zhao, Qingzhe Li, Negar Etemadyrad, Xiaojie Guo

On the other hand, graph topological evolution has been investigated in the graph signal processing domain historically, but it involves intensive labors to manually determine suitable prescribed spectral models and prohibitive difficulty to fit their potential combinations and compositions.

Graph Learning

Multi-stage Deep Classifier Cascades for Open World Recognition

1 code implementation26 Aug 2019 Xiaojie Guo, Amir Alipour-Fanid, Lingfei Wu, Hemant Purohit, Xiang Chen, Kai Zeng, Liang Zhao

At present, object recognition studies are mostly conducted in a closed lab setting with classes in test phase typically in training phase.

Object Recognition

Kindling the Darkness: A Practical Low-light Image Enhancer

4 code implementations4 May 2019 Yonghua Zhang, Jiawan Zhang, Xiaojie Guo

It is worth to note that our network is trained with paired images shot under different exposure conditions, instead of using any ground-truth reflectance and illumination information.

Low-Light Image Enhancement

Single Image Deraining: A Comprehensive Benchmark Analysis

1 code implementation CVPR 2019 Siyuan Li, Iago Breno Araujo, Wenqi Ren, Zhangyang Wang, Eric K. Tokuda, Roberto Hirata Junior, Roberto Cesar-Junior, Jiawan Zhang, Xiaojie Guo, Xiaochun Cao

We present a comprehensive study and evaluation of existing single image deraining algorithms, using a new large-scale benchmark consisting of both synthetic and real-world rainy images. This dataset highlights diverse data sources and image contents, and is divided into three subsets (rain streak, rain drop, rain and mist), each serving different training or evaluation purposes.

Single Image Deraining

PFLD: A Practical Facial Landmark Detector

18 code implementations28 Feb 2019 Xiaojie Guo, Siyuan Li, Jinke Yu, Jiawan Zhang, Jiayi Ma, Lin Ma, Wei Liu, Haibin Ling

Being accurate, efficient, and compact is essential to a facial landmark detector for practical use.

Face Alignment Facial Landmark Detection

Deep Graph Translation

2 code implementations25 May 2018 Xiaojie Guo, Lingfei Wu, Liang Zhao

To achieve this, we propose a novel Graph-Translation-Generative Adversarial Networks (GT-GAN) which will generate a graph translator from input to target graphs.

Management Translation

Fast Single Image Rain Removal via a Deep Decomposition-Composition Network

no code implementations8 Apr 2018 Siyuan LI, Wenqi Ren, Jiawan Zhang, Jinke Yu, Xiaojie Guo

Rain effect in images typically is annoying for many multimedia and computer vision tasks.

Rain Removal

LIME: Low-light Image Enhancement via Illumination Map Estimation

2 code implementations IEEE TIP 2016 Xiaojie Guo, Yu Li, Haibin Ling

When one captures images in low-light conditions, the images often suffer from low visibility.

 Ranked #1 on Low-Light Image Enhancement on 10 Monkey Species (using extra training data)

Low-Light Image Enhancement

LIME: A Method for Low-light IMage Enhancement

no code implementations17 May 2016 Xiaojie Guo

When one captures images in low-light conditions, the images often suffer from low visibility.

Low-Light Image Enhancement

Exclusivity Regularized Machine

no code implementations28 Mar 2016 Xiaojie Guo

It has been recognized that the diversity of base learners is of utmost importance to a good ensemble.

Adaptively Unified Semi-Supervised Dictionary Learning With Active Points

no code implementations ICCV 2015 Xiaobo Wang, Xiaojie Guo, Stan Z. Li

In this paper, we present a novel semi-supervised dictionary learning method, which uses the informative coding vectors of both labeled and unlabeled data, and adaptively emphasizes the high confidence coding vectors of unlabeled data to enhance the dictionary discriminative capability simultaneously.

Dictionary Learning

Visual Data Deblocking using Structural Layer Priors

no code implementations6 Jul 2015 Xiaojie Guo

The blocking artifact frequently appears in compressed real-world images or video sequences, especially coded at low bit rates, which is visually annoying and likely hurts the performance of many computer vision algorithms.


Generalized Tensor Total Variation Minimization for Visual Data Recovery

no code implementations CVPR 2015 Xiaojie Guo, Yi Ma

In this paper, we propose a definition of Generalized Tensor Total Variation norm (GTV) that considers both the inhomogeneity and the multi-directionality of responses to derivative-like filters.


Robust Separation of Reflection from Multiple Images

no code implementations CVPR 2014 Xiaojie Guo, Xiaochun Cao, Yi Ma

When one records a video/image sequence through a transparent medium (e. g. glass), the image is often a superposition of a transmitted layer (scene behind the medium) and a reflected layer.

Video Editing with Temporal, Spatial and Appearance Consistency

no code implementations CVPR 2013 Xiaojie Guo, Xiaochun Cao, Xiaowu Chen, Yi Ma

Given an area of interest in a video sequence, one may want to manipulate or edit the area, e. g. remove occlusions from or replace with an advertisement on it.

Image Matting Video Editing

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