Search Results for author: Yao Li

Found 67 papers, 16 papers with code

Uniformly Accelerated Motion Model for Inter Prediction

no code implementations16 Jul 2024 Zhuoyuan Li, Yao Li, Chuanbo Tang, Li Li, Dong Liu, Feng Wu

To address these issues, we introduce a uniformly accelerated motion model (UAMM) to exploit motion-related elements (velocity, acceleration) of moving objects between the video frames, and further combine them to assist the inter prediction methods to handle the variable motion in the temporal domain.

Motion Compensation Motion Estimation

In-Loop Filtering via Trained Look-Up Tables

no code implementations15 Jul 2024 Zhuoyuan Li, Jiacheng Li, Yao Li, Li Li, Dong Liu, Feng Wu

Recently, neural network-based in-loop filtering methods achieve remarkable coding gains beyond the capability of advanced video coding standards, which becomes a powerful coding tool candidate for future video coding standards.

Image Restoration

IVCA: Inter-Relation-Aware Video Complexity Analyzer

no code implementations29 Jun 2024 Junqi Liao, Yao Li, Zhuoyuan Li, Li Li, Dong Liu

To meet the real-time analysis requirements of video streaming applications, we propose an inter-relation-aware video complexity analyzer (IVCA) as an extension to VCA.

Motion Estimation Relation

Modeling, Inference, and Prediction in Mobility-Based Compartmental Models for Epidemiology

no code implementations17 Jun 2024 Ning Jiang, Weiqi Chu, Yao Li

Classical compartmental models in epidemiology often struggle to accurately capture real-world dynamics due to their inability to address the inherent heterogeneity of populations.

Epidemiology Time Series

Perturbation Towards Easy Samples Improves Targeted Adversarial Transferability

1 code implementation NeurIPS 2023 Junqi Gao, Biqing Qi, Yao Li, Zhichang Guo, Dong Li, Yuming Xing, Dazhi Zhang

Based on the above facts, we verified that adding perturbations to easy samples in the target class improves targeted adversarial transferability of existing attack methods.

Density Estimation

Improving Logits-based Detector without Logits from Black-box LLMs

no code implementations7 Jun 2024 Cong Zeng, Shengkun Tang, Xianjun Yang, Yuanzhou Chen, Yiyou Sun, Zhiqiang Xu, Yao Li, Haifeng Chen, Wei Cheng, Dongkuan Xu

However, these methods grapple with the misalignment between the distributions of the surrogate and the often undisclosed target models, leading to performance degradation, particularly with the introduction of new, closed-source models.

Text Detection Text Generation

Region of Interest Detection in Melanocytic Skin Tumor Whole Slide Images -- Nevus & Melanoma

1 code implementation16 May 2024 Yi Cui, Yao Li, Jayson R. Miedema, Sharon N. Edmiston, Sherif Farag, J. S. Marron, Nancy E. Thomas

Automated region of interest detection in histopathological image analysis is a challenging and important topic with tremendous potential impact on clinical practice.

medical image detection whole slide images

DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

1 code implementation7 May 2024 DeepSeek-AI, Aixin Liu, Bei Feng, Bin Wang, Bingxuan Wang, Bo Liu, Chenggang Zhao, Chengqi Dengr, Chong Ruan, Damai Dai, Daya Guo, Dejian Yang, Deli Chen, Dongjie Ji, Erhang Li, Fangyun Lin, Fuli Luo, Guangbo Hao, Guanting Chen, Guowei Li, H. Zhang, Hanwei Xu, Hao Yang, Haowei Zhang, Honghui Ding, Huajian Xin, Huazuo Gao, Hui Li, Hui Qu, J. L. Cai, Jian Liang, JianZhong Guo, Jiaqi Ni, Jiashi Li, Jin Chen, Jingyang Yuan, Junjie Qiu, Junxiao Song, Kai Dong, Kaige Gao, Kang Guan, Lean Wang, Lecong Zhang, Lei Xu, Leyi Xia, Liang Zhao, Liyue Zhang, Meng Li, Miaojun Wang, Mingchuan Zhang, Minghua Zhang, Minghui Tang, Mingming Li, Ning Tian, Panpan Huang, Peiyi Wang, Peng Zhang, Qihao Zhu, Qinyu Chen, Qiushi Du, R. J. Chen, R. L. Jin, Ruiqi Ge, Ruizhe Pan, Runxin Xu, Ruyi Chen, S. S. Li, Shanghao Lu, Shangyan Zhou, Shanhuang Chen, Shaoqing Wu, Shengfeng Ye, Shirong Ma, Shiyu Wang, Shuang Zhou, Shuiping Yu, Shunfeng Zhou, Size Zheng, T. Wang, Tian Pei, Tian Yuan, Tianyu Sun, W. L. Xiao, Wangding Zeng, Wei An, Wen Liu, Wenfeng Liang, Wenjun Gao, Wentao Zhang, X. Q. Li, Xiangyue Jin, Xianzu Wang, Xiao Bi, Xiaodong Liu, Xiaohan Wang, Xiaojin Shen, Xiaokang Chen, Xiaosha Chen, Xiaotao Nie, Xiaowen Sun, Xiaoxiang Wang, Xin Liu, Xin Xie, Xingkai Yu, Xinnan Song, Xinyi Zhou, Xinyu Yang, Xuan Lu, Xuecheng Su, Y. Wu, Y. K. Li, Y. X. Wei, Y. X. Zhu, Yanhong Xu, Yanping Huang, Yao Li, Yao Zhao, Yaofeng Sun, Yaohui Li, Yaohui Wang, Yi Zheng, Yichao Zhang, Yiliang Xiong, Yilong Zhao, Ying He, Ying Tang, Yishi Piao, Yixin Dong, Yixuan Tan, Yiyuan Liu, Yongji Wang, Yongqiang Guo, Yuchen Zhu, Yuduan Wang, Yuheng Zou, Yukun Zha, Yunxian Ma, Yuting Yan, Yuxiang You, Yuxuan Liu, Z. Z. Ren, Zehui Ren, Zhangli Sha, Zhe Fu, Zhen Huang, Zhen Zhang, Zhenda Xie, Zhewen Hao, Zhihong Shao, Zhiniu Wen, Zhipeng Xu, Zhongyu Zhang, Zhuoshu Li, Zihan Wang, Zihui Gu, Zilin Li, Ziwei Xie

MLA guarantees efficient inference through significantly compressing the Key-Value (KV) cache into a latent vector, while DeepSeekMoE enables training strong models at an economical cost through sparse computation.

Language Modelling Reinforcement Learning (RL)

NTIRE 2024 Quality Assessment of AI-Generated Content Challenge

no code implementations25 Apr 2024 Xiaohong Liu, Xiongkuo Min, Guangtao Zhai, Chunyi Li, Tengchuan Kou, Wei Sun, HaoNing Wu, Yixuan Gao, Yuqin Cao, ZiCheng Zhang, Xiele Wu, Radu Timofte, Fei Peng, Huiyuan Fu, Anlong Ming, Chuanming Wang, Huadong Ma, Shuai He, Zifei Dou, Shu Chen, Huacong Zhang, Haiyi Xie, Chengwei Wang, Baoying Chen, Jishen Zeng, Jianquan Yang, Weigang Wang, Xi Fang, Xiaoxin Lv, Jun Yan, Tianwu Zhi, Yabin Zhang, Yaohui Li, Yang Li, Jingwen Xu, Jianzhao Liu, Yiting Liao, Junlin Li, Zihao Yu, Yiting Lu, Xin Li, Hossein Motamednia, S. Farhad Hosseini-Benvidi, Fengbin Guan, Ahmad Mahmoudi-Aznaveh, Azadeh Mansouri, Ganzorig Gankhuyag, Kihwan Yoon, Yifang Xu, Haotian Fan, Fangyuan Kong, Shiling Zhao, Weifeng Dong, Haibing Yin, Li Zhu, Zhiling Wang, Bingchen Huang, Avinab Saha, Sandeep Mishra, Shashank Gupta, Rajesh Sureddi, Oindrila Saha, Luigi Celona, Simone Bianco, Paolo Napoletano, Raimondo Schettini, Junfeng Yang, Jing Fu, Wei zhang, Wenzhi Cao, Limei Liu, Han Peng, Weijun Yuan, Zhan Li, Yihang Cheng, Yifan Deng, Haohui Li, Bowen Qu, Yao Li, Shuqing Luo, Shunzhou Wang, Wei Gao, Zihao Lu, Marcos V. Conde, Xinrui Wang, Zhibo Chen, Ruling Liao, Yan Ye, Qiulin Wang, Bing Li, Zhaokun Zhou, Miao Geng, Rui Chen, Xin Tao, Xiaoyu Liang, Shangkun Sun, Xingyuan Ma, Jiaze Li, Mengduo Yang, Haoran Xu, Jie zhou, Shiding Zhu, Bohan Yu, Pengfei Chen, Xinrui Xu, Jiabin Shen, Zhichao Duan, Erfan Asadi, Jiahe Liu, Qi Yan, Youran Qu, Xiaohui Zeng, Lele Wang, Renjie Liao

A total of 196 participants have registered in the video track.

Image Quality Assessment Image Restoration +2

CORP: A Multi-Modal Dataset for Campus-Oriented Roadside Perception Tasks

no code implementations4 Apr 2024 Beibei Wang, Shuang Meng, Lu Zhang, Chenjie Wang, Jingjing Huang, Yao Li, Haojie Ren, Yuxuan Xiao, Yuru Peng, Jianmin Ji, Yu Zhang, Yanyong Zhang

Numerous roadside perception datasets have been introduced to propel advancements in autonomous driving and intelligent transportation systems research and development.

Autonomous Driving Instance Segmentation +1

Inverse Optimal Control for Linear Quadratic Tracking with Unknown Target States

no code implementations27 Feb 2024 Yao Li, Chengpu Yu, Hao Fang, Jie Chen

A computationally efficient and numerically reliable parameter identification algorithm is proposed by equating optimal control strategies with a system of linear equations, and the associated relative error upper bound is derived in terms of data volume and signal-to-noise ratio.

Adversarial Training for Physics-Informed Neural Networks

1 code implementation18 Oct 2023 Yao Li, Shengzhu Shi, Zhichang Guo, Boying Wu

AT-PINNs enhance the robustness of PINNs by fine-tuning the model with adversarial samples, which can accurately identify model failure locations and drive the model to focus on those regions during training.

Adversarial Attack

AdaDiff: Accelerating Diffusion Models through Step-Wise Adaptive Computation

no code implementations29 Sep 2023 Shengkun Tang, Yaqing Wang, Caiwen Ding, Yi Liang, Yao Li, Dongkuan Xu

Unlike typical adaptive computation challenges that deal with single-step generation problems, diffusion processes with a multi-step generation need to dynamically adjust their computational resource allocation based on the ongoing assessment of each step's importance to the final image output, presenting a unique set of challenges.

text-guided-generation

MiChao-HuaFen 1.0: A Specialized Pre-trained Corpus Dataset for Domain-specific Large Models

no code implementations21 Sep 2023 Yidong Liu, FuKai Shang, Fang Wang, Rui Xu, Jun Wang, Wei Li, Yao Li, Conghui He

With the advancement of deep learning technologies, general-purpose large models such as GPT-4 have demonstrated exceptional capabilities across various domains.

A Review of Adversarial Attacks in Computer Vision

no code implementations15 Aug 2023 Yutong Zhang, Yao Li, Yin Li, Zhichang Guo

Deep neural networks have been widely used in various downstream tasks, especially those safety-critical scenario such as autonomous driving, but deep networks are often threatened by adversarial samples.

Autonomous Driving

Artificial Neural Network Prediction of COVID-19 Daily Infection Count

no code implementations23 Jun 2023 Ning Jiang, Charles Kolozsvary, Yao Li

It is well known that the confirmed COVID-19 infection is only a fraction of the true fraction.

Bi-LRFusion: Bi-Directional LiDAR-Radar Fusion for 3D Dynamic Object Detection

1 code implementation CVPR 2023 Yingjie Wang, Jiajun Deng, Yao Li, Jinshui Hu, Cong Liu, Yu Zhang, Jianmin Ji, Wanli Ouyang, Yanyong Zhang

LiDAR and Radar are two complementary sensing approaches in that LiDAR specializes in capturing an object's 3D shape while Radar provides longer detection ranges as well as velocity hints.

object-detection Object Detection

CTSN: Predicting Cloth Deformation for Skeleton-based Characters with a Two-stream Skinning Network

no code implementations30 May 2023 Yudi Li, Min Tang, Yun Yang, Ruofeng Tong, Shuangcai Yang, Yao Li, Bailin An, Qilong Kou

We present a novel learning method to predict the cloth deformation for skeleton-based characters with a two-stream network.

Stationary Point Losses for Robust Model

no code implementations19 Feb 2023 Weiwei Gao, Dazhi Zhang, Yao Li, Zhichang Guo, Ovanes Petrosian

CE loss sharpens the neural network at the decision boundary to achieve a lower loss, rather than pushing the boundary to a more robust position.

TrajMatch: Towards Automatic Spatio-temporal Calibration for Roadside LiDARs through Trajectory Matching

no code implementations4 Feb 2023 Haojie Ren, Sha Zhang, Sugang Li, Yao Li, Xinchen Li, Jianmin Ji, Yu Zhang, Yanyong Zhang

In this paper, we propose TrajMatch -- the first system that can automatically calibrate for roadside LiDARs in both time and space.

Accelerating Dataset Distillation via Model Augmentation

2 code implementations CVPR 2023 Lei Zhang, Jie Zhang, Bowen Lei, Subhabrata Mukherjee, Xiang Pan, Bo Zhao, Caiwen Ding, Yao Li, Dongkuan Xu

Dataset Distillation (DD), a newly emerging field, aims at generating much smaller but efficient synthetic training datasets from large ones.

Dataset Distillation

You Need Multiple Exiting: Dynamic Early Exiting for Accelerating Unified Vision Language Model

1 code implementation CVPR 2023 Shengkun Tang, Yaqing Wang, Zhenglun Kong, Tianchi Zhang, Yao Li, Caiwen Ding, Yanzhi Wang, Yi Liang, Dongkuan Xu

To handle this challenge, we propose a novel early exiting strategy for unified visual language models, which allows dynamically skip the layers in encoder and decoder simultaneously in term of input layer-wise similarities with multiple times of early exiting, namely \textbf{MuE}.

Decoder Language Modelling

Region of Interest Detection in Melanocytic Skin Tumor Whole Slide Images

no code implementations29 Oct 2022 Yi Cui, Yao Li, Jayson R. Miedema, Sherif Farag, J. S. Marron, Nancy E. Thomas

Even though we test the experiments on the skin tumor dataset, our work could also be extended to other medical image detection problems, such as various tumors' classification and prediction, to help and benefit the clinical evaluation and diagnosis of different tumors.

medical image detection whole slide images

ADDMU: Detection of Far-Boundary Adversarial Examples with Data and Model Uncertainty Estimation

1 code implementation22 Oct 2022 Fan Yin, Yao Li, Cho-Jui Hsieh, Kai-Wei Chang

Finally, our analysis shows that the two types of uncertainty provided by \textbf{ADDMU} can be leveraged to characterize adversarial examples and identify the ones that contribute most to model's robustness in adversarial training.

Supervised Parameter Estimation of Neuron Populations from Multiple Firing Events

no code implementations2 Oct 2022 Long Le, Yao Li

In this paper, we study an automatic approach of learning the parameters of neuron populations from a training set consisting of pairs of spiking series and parameter labels via supervised learning.

Forecasting SQL Query Cost at Twitter

1 code implementation12 Apr 2022 Chunxu Tang, Beinan Wang, Zhenxiao Luo, Huijun Wu, Shajan Dasan, Maosong Fu, Yao Li, Mainak Ghosh, Ruchin Kabra, Nikhil Kantibhai Navadiya, Da Cheng, Fred Dai, Vrushali Channapattan, Prachi Mishra

We propose a SQL query cost predictor service, which employs machine learning techniques to train models from historical query request logs and rapidly forecasts the CPU and memory resource usages of online queries without any computation in a SQL engine.

Scheduling

N-Cloth: Predicting 3D Cloth Deformation with Mesh-Based Networks

no code implementations13 Dec 2021 Yudi Li, Min Tang, Yun Yang, Zi Huang, Ruofeng Tong, Shuangcai Yang, Yao Li, Dinesh Manocha

We present a novel mesh-based learning approach (N-Cloth) for plausible 3D cloth deformation prediction.

A Review of Adversarial Attack and Defense for Classification Methods

1 code implementation18 Nov 2021 Yao Li, Minhao Cheng, Cho-Jui Hsieh, Thomas C. M. Lee

Despite the efficiency and scalability of machine learning systems, recent studies have demonstrated that many classification methods, especially deep neural networks (DNNs), are vulnerable to adversarial examples; i. e., examples that are carefully crafted to fool a well-trained classification model while being indistinguishable from natural data to human.

Adversarial Attack Classification

Decentralized Composite Optimization with Compression

no code implementations10 Aug 2021 Yao Li, Xiaorui Liu, Jiliang Tang, Ming Yan, Kun Yuan

Decentralized optimization and communication compression have exhibited their great potential in accelerating distributed machine learning by mitigating the communication bottleneck in practice.

Neighbor-Vote: Improving Monocular 3D Object Detection through Neighbor Distance Voting

1 code implementation6 Jul 2021 Xiaomeng Chu, Jiajun Deng, Yao Li, Zhenxun Yuan, Yanyong Zhang, Jianmin Ji, Yu Zhang

As cameras are increasingly deployed in new application domains such as autonomous driving, performing 3D object detection on monocular images becomes an important task for visual scene understanding.

Autonomous Driving Monocular 3D Object Detection +4

Adversarial Examples Detection with Bayesian Neural Network

1 code implementation18 May 2021 Yao Li, Tongyi Tang, Cho-Jui Hsieh, Thomas C. M. Lee

In this paper, we propose a new framework to detect adversarial examples motivated by the observations that random components can improve the smoothness of predictors and make it easier to simulate the output distribution of a deep neural network.

$\rm ^{83}Rb$/$\rm ^{83m}Kr$ production and cross-section measurement with 3.4 MeV and 20 MeV proton beams

no code implementations4 Feb 2021 Dan Zhang, Jingkai Xia, YiFan Li, Jingtao You, Yao Li, Changbo Fu, Jianglai Liu, Ning Zhou, Jie Bao, Huan Jia, Chenzhang Yuan, Yuan He, Weixing Xiong, Mengyun Guan

$\rm ^{83m}Kr$, with a short lifetime, is an ideal calibration source for liquid xenon or liquid argon detectors.

Nuclear Experiment Instrumentation and Detectors

Cross-Patch Graph Convolutional Network for Image Denoising

no code implementations ICCV 2021 Yao Li, Xueyang Fu, Zheng-Jun Zha

However, the real noisy images in practical are mostly of high resolution rather than the cropped small patches and the vanilla training strategies ignore the cross-patch contextual dependency in the whole image.

Image Denoising

Super interference fringes of two-photon photoluminescence in individual Au nanoparticles: the critical role of the intermediate state

no code implementations24 Dec 2020 Yao Li, Yonggang Yang, Chengbing Qin, Yunrui Song, Shuangping Han, Guofeng Zhang, Ruiyun Chen, Jianyong Hu, Liantuan Xiao, Suotang Jia

Here, we presented two-photon photoluminescence (TPPL) measurements on individual Au nanobipyramids (AuNP) to reveal their ultrafast dynamics by two-pulse excitation on a global time scale ranging from sub-femtosecond to tens of picoseconds.

Optics Mesoscale and Nanoscale Physics Quantum Physics

A deep learning based interactive sketching system for fashion images design

no code implementations9 Oct 2020 Yao Li, Xianggang Yu, Xiaoguang Han, Nianjuan Jiang, Kui Jia, Jiangbo Lu

In this work, we propose an interactive system to design diverse high-quality garment images from fashion sketches and the texture information.

Intrinsic Image Decomposition Texture Synthesis

Towards Better Opioid Antagonists Using Deep Reinforcement Learning

no code implementations26 Mar 2020 Jianyuan Deng, Zhibo Yang, Yao Li, Dimitris Samaras, Fusheng Wang

Naloxone, an opioid antagonist, has been widely used to save lives from opioid overdose, a leading cause for death in the opioid epidemic.

Drug Discovery reinforcement-learning +2

Stationary distributions of persistent ecological systems

no code implementations9 Mar 2020 Alexandru Hening, Yao Li

We highlight new biological insights by analyzing the stationary distributions of the ecosystems and by seeing how various types of environmental fluctuations influence the long term fate of populations.

A Double Residual Compression Algorithm for Efficient Distributed Learning

no code implementations16 Oct 2019 Xiaorui Liu, Yao Li, Jiliang Tang, Ming Yan

Large-scale machine learning models are often trained by parallel stochastic gradient descent algorithms.

Defending Against Adversarial Examples by Regularized Deep Embedding

no code implementations25 Sep 2019 Yao Li, Martin Renqiang Min, Wenchao Yu, Cho-Jui Hsieh, Thomas Lee, Erik Kruus

Recent studies have demonstrated the vulnerability of deep convolutional neural networks against adversarial examples.

Adversarial Attack Adversarial Robustness

Improve variational autoEncoder with auxiliary softmax multiclassifier

no code implementations17 Aug 2019 Yao Li

As a general-purpose generation model, the vanilla VAE can not fit well with various data sets and neural networks with different structures.

On linear convergence of two decentralized algorithms

no code implementations17 Jun 2019 Yao Li, Ming Yan

In addition, we relax the requirement for the objective functions and the mixing matrices.

Vocal Bursts Valence Prediction

Learning from Group Comparisons: Exploiting Higher Order Interactions

no code implementations NeurIPS 2018 Yao Li, Minhao Cheng, Kevin Fujii, Fushing Hsieh, Cho-Jui Hsieh

We study the problem of learning from group comparisons, with applications in predicting outcomes of sports and online games.

Image Super-Resolution Using VDSR-ResNeXt and SRCGAN

no code implementations10 Oct 2018 Saifuddin Hitawala, Yao Li, Xian Wang, Dongyang Yang

Over the past decade, many Super Resolution techniques have been developed using deep learning.

Image Super-Resolution

Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network

1 code implementation ICLR 2019 Xuanqing Liu, Yao Li, Chongruo wu, Cho-Jui Hsieh

Instead, we model randomness under the framework of Bayesian Neural Network (BNN) to formally learn the posterior distribution of models in a scalable way.

Adversarial Defense

Adversarial 3D Human Pose Estimation via Multimodal Depth Supervision

no code implementations21 Sep 2018 Kun Zhou, Jinmiao Cai, Yao Li, Yulong Shi, Xiaoguang Han, Nianjuan Jiang, Kui Jia, Jiangbo Lu

In this paper, a novel deep-learning based framework is proposed to infer 3D human poses from a single image.

3D Human Pose Estimation

Deep Descriptor Transforming for Image Co-Localization

no code implementations8 May 2017 Xiu-Shen Wei, Chen-Lin Zhang, Yao Li, Chen-Wei Xie, Jianxin Wu, Chunhua Shen, Zhi-Hua Zhou

Reusable model design becomes desirable with the rapid expansion of machine learning applications.

Scalable Demand-Aware Recommendation

no code implementations NeurIPS 2017 Jinfeng Yi, Cho-Jui Hsieh, Kush Varshney, Lijun Zhang, Yao Li

In particular for durable goods, time utility is a function of inter-purchase duration within product category because consumers are unlikely to purchase two items in the same category in close temporal succession.

Image Co-localization by Mimicking a Good Detector's Confidence Score Distribution

no code implementations15 Mar 2016 Yao Li, Linqiao Liu, Chunhua Shen, Anton Van Den Hengel

More specifically, we observe that given a set of object proposals extracted from an image that contains the object of interest, an accurate strongly supervised object detector should give high scores to only a small minority of proposals, and low scores to most of them.

Object

Mining Mid-level Visual Patterns with Deep CNN Activations

1 code implementation21 Jun 2015 Yao Li, Lingqiao Liu, Chunhua Shen, Anton Van Den Hengel

The purpose of mid-level visual element discovery is to find clusters of image patches that are both representative and discriminative.

Iterative Neural Autoregressive Distribution Estimator NADE-k

1 code implementation NeurIPS 2014 Tapani Raiko, Yao Li, Kyunghyun Cho, Yoshua Bengio

Training of the neural autoregressive density estimator (NADE) can be viewed as doing one step of probabilistic inference on missing values in data.

Density Estimation Image Generation +1

Mid-level Deep Pattern Mining

no code implementations CVPR 2015 Yao Li, Lingqiao Liu, Chunhua Shen, Anton Van Den Hengel

We apply our approach to scene and object classification tasks, and demonstrate that our approach outperforms all previous works on mid-level visual element discovery by a sizeable margin with far fewer elements being used.

Contextual Hypergraph Modelling for Salient Object Detection

no code implementations22 Oct 2013 Xi Li, Yao Li, Chunhua Shen, Anthony Dick, Anton Van Den Hengel

In this work, we model an image as a hypergraph that utilizes a set of hyperedges to capture the contextual properties of image pixels or regions.

Object object-detection +2

Characterness: An Indicator of Text in the Wild

no code implementations25 Sep 2013 Yao Li, Wenjing Jia, Chunhua Shen, Anton Van Den Hengel

In order to measure the characterness we develop three novel cues that are tailored for character detection, and a Bayesian method for their integration.

Saliency Detection Scene Text Detection +1

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