Search Results for author: Rui Zhao

Found 120 papers, 36 papers with code

RBF-Softmax: Learning Deep Representative Prototypes with Radial Basis Function Softmax

1 code implementation ECCV 2020 Xiao Zhang, Rui Zhao, Yu Qiao, Hongsheng Li

To address this problem, this paper introduces a novel Radial Basis Function (RBF) distances to replace the commonly used inner products in the softmax loss function, such that it can adaptively assign losses to regularize the intra-class and inter-class distances by reshaping the relative differences, and thus creating more representative prototypes of classes to improve optimization.

Better Aligning Text-to-Image Models with Human Preference

no code implementations25 Mar 2023 Xiaoshi Wu, Keqiang Sun, Feng Zhu, Rui Zhao, Hongsheng Li

Using the HPS, we propose a simple yet effective method to adapt Stable Diffusion to better align with human aesthetic preferences.

MoWE: Mixture of Weather Experts for Multiple Adverse Weather Removal

no code implementations24 Mar 2023 Yulin Luo, Rui Zhao, Xiaobao Wei, Jinwei Chen, Yijie Lu, Shenghao Xie, Tianyu Wang, Ruiqin Xiong, Ming Lu, Shanghang Zhang

Our MoWE achieves SOTA performance in upstream task on the proposed dataset and two public datasets, i. e. All-Weather and Rain/Fog-Cityscapes, and also have better perceptual results in downstream segmentation task compared to other methods.

Autonomous Driving Rain Removal

CORA: Adapting CLIP for Open-Vocabulary Detection with Region Prompting and Anchor Pre-Matching

1 code implementation23 Mar 2023 Xiaoshi Wu, Feng Zhu, Rui Zhao, Hongsheng Li

To overcome these obstacles, we propose CORA, a DETR-style framework that adapts CLIP for Open-vocabulary detection by Region prompting and Anchor pre-matching.

 Ranked #1 on Open Vocabulary Object Detection on MSCOCO (using extra training data)

object-detection Object Localization +1

Explore the Power of Synthetic Data on Few-shot Object Detection

no code implementations23 Mar 2023 Shaobo Lin, Kun Wang, Xingyu Zeng, Rui Zhao

To construct a representative synthetic training dataset, we maximize the diversity of the selected images via a sample-based and cluster-based method.

Few-Shot Object Detection object-detection +2

SpikeCV: Open a Continuous Computer Vision Era

1 code implementation21 Mar 2023 Yajing Zheng, Jiyuan Zhang, Rui Zhao, Jianhao Ding, Shiyan Chen, Ruiqin Xiong, Zhaofei Yu, Tiejun Huang

SpikeCV focuses on encapsulation for spike data, standardization for dataset interfaces, modularization for vision tasks, and real-time applications for challenging scenes.

HumanBench: Towards General Human-centric Perception with Projector Assisted Pretraining

no code implementations10 Mar 2023 Shixiang Tang, Cheng Chen, Qingsong Xie, Meilin Chen, Yizhou Wang, Yuanzheng Ci, Lei Bai, Feng Zhu, Haiyang Yang, Li Yi, Rui Zhao, Wanli Ouyang

Specifically, we propose a \textbf{HumanBench} based on existing datasets to comprehensively evaluate on the common ground the generalization abilities of different pretraining methods on 19 datasets from 6 diverse downstream tasks, including person ReID, pose estimation, human parsing, pedestrian attribute recognition, pedestrian detection, and crowd counting.

Autonomous Driving Crowd Counting +4

UniHCP: A Unified Model for Human-Centric Perceptions

1 code implementation6 Mar 2023 Yuanzheng Ci, Yizhou Wang, Meilin Chen, Shixiang Tang, Lei Bai, Feng Zhu, Rui Zhao, Fengwei Yu, Donglian Qi, Wanli Ouyang

When adapted to a specific task, UniHCP achieves new SOTAs on a wide range of human-centric tasks, e. g., 69. 8 mIoU on CIHP for human parsing, 86. 18 mA on PA-100K for attribute prediction, 90. 3 mAP on Market1501 for ReID, and 85. 8 JI on CrowdHuman for pedestrian detection, performing better than specialized models tailored for each task.

Human Parsing Pedestrian Detection +2

Zero-Shot Text-to-Parameter Translation for Game Character Auto-Creation

no code implementations2 Mar 2023 Rui Zhao, Wei Li, Zhipeng Hu, Lincheng Li, Zhengxia Zou, Zhenwei Shi, Changjie Fan

In our method, taking the power of large-scale pre-trained multi-modal CLIP and neural rendering, T2P searches both continuous facial parameters and discrete facial parameters in a unified framework.

Face Model Neural Rendering +2

An Effective Crop-Paste Pipeline for Few-shot Object Detection

no code implementations28 Feb 2023 Shaobo Lin, Kun Wang, Xingyu Zeng, Rui Zhao

Specifically, we first discover the base images which contain the FP of novel categories and select a certain amount of samples from them for the base and novel categories balance.

Data Augmentation Few-Shot Object Detection +1

Efficient Masked Autoencoders with Self-Consistency

no code implementations28 Feb 2023 Zhaowen Li, Yousong Zhu, Zhiyang Chen, Wei Li, Chaoyang Zhao, Liwei Wu, Rui Zhao, Ming Tang, Jinqiao Wang

However, its high random mask ratio would result in two serious problems: 1) the data are not efficiently exploited, which brings inefficient pre-training (\eg, 1600 epochs for MAE $vs.$ 300 epochs for the supervised), and 2) the high uncertainty and inconsistency of the pre-trained model, \ie, the prediction of the same patch may be inconsistent under different mask rounds.

Language Modelling Masked Language Modeling +3

Saliency Guided Contrastive Learning on Scene Images

no code implementations22 Feb 2023 Meilin Chen, Yizhou Wang, Shixiang Tang, Feng Zhu, Haiyang Yang, Lei Bai, Rui Zhao, Donglian Qi, Wanli Ouyang

Despite being feasible, recent works largely overlooked discovering the most discriminative regions for contrastive learning to object representations in scene images.

Contrastive Learning Representation Learning +1

Exploring Stochastic Autoregressive Image Modeling for Visual Representation

1 code implementation3 Dec 2022 Yu Qi, Fan Yang, Yousong Zhu, Yufei Liu, Liwei Wu, Rui Zhao, Wei Li

By introducing stochastic prediction and the parallel encoder-decoder, SAIM significantly improve the performance of autoregressive image modeling.

Self-Supervised Learning

PUnifiedNER: A Prompting-based Unified NER System for Diverse Datasets

no code implementations27 Nov 2022 Jinghui Lu, Rui Zhao, Brian Mac Namee, Fei Tan

In this work, we present a ``versatile'' model -- the Prompting-based Unified NER system (PUnifiedNER) -- that works with data from different domains and can recognise up to 37 entity types simultaneously, and theoretically it could be as many as possible.

named-entity-recognition Named Entity Recognition +1

MIAD: A Maintenance Inspection Dataset for Unsupervised Anomaly Detection

no code implementations25 Nov 2022 Tianpeng Bao, Jiadong Chen, Wei Li, Xiang Wang, Jingjing Fei, Liwei Wu, Rui Zhao, Ye Zheng

However, existing datasets for unsupervised anomaly detection are biased towards manufacturing inspection, not considering maintenance inspection which is usually conducted under outdoor uncontrolled environment such as varying camera viewpoints, messy background and degradation of object surface after long-term working.

Unsupervised Anomaly Detection

LongFNT: Long-form Speech Recognition with Factorized Neural Transducer

no code implementations17 Nov 2022 Xun Gong, Yu Wu, Jinyu Li, Shujie Liu, Rui Zhao, Xie Chen, Yanmin Qian

This motivates us to leverage the factorized neural transducer structure, containing a real language model, the vocabulary predictor.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +2

Geo6D: Geometric Constraints Learning for 6D Pose Estimation

no code implementations20 Oct 2022 Jianqiu Chen, Mingshan Sun, Ye Zheng, Tianpeng Bao, Zhenyu He, Donghai Li, Guoqiang Jin, Rui Zhao, Liwei Wu, Xiaoke Jiang

Existing direct 6D pose estimation methods regress target 6D poses without the need for post-processing, making them effective and easy to develop.

6D Pose Estimation object-detection +3

A Unified Framework with Meta-dropout for Few-shot Learning

no code implementations12 Oct 2022 Shaobo Lin, Xingyu Zeng, Rui Zhao

Conventional training of deep neural networks usually requires a substantial amount of data with expensive human annotations.

Few-Shot Image Classification Few-Shot Learning +2

What Makes Pre-trained Language Models Better Zero/Few-shot Learners?

no code implementations30 Sep 2022 Jinghui Lu, Rui Zhao, Brian Mac Namee, Dongsheng Zhu, Weidong Han, Fei Tan

In this paper, we propose a theoretical framework to explain the efficacy of prompt learning in zero/few-shot scenarios.

Language Modelling

Obj2Seq: Formatting Objects as Sequences with Class Prompt for Visual Tasks

2 code implementations28 Sep 2022 Zhiyang Chen, Yousong Zhu, Zhaowen Li, Fan Yang, Wei Li, Haixin Wang, Chaoyang Zhao, Liwei Wu, Rui Zhao, Jinqiao Wang, Ming Tang

Obj2Seq is able to flexibly determine input categories to satisfy customized requirements, and be easily extended to different visual tasks.

Multi-Label Classification Object Detection +1

Jointly Contrastive Representation Learning on Road Network and Trajectory

1 code implementation14 Sep 2022 Zhenyu Mao, Ziyue Li, Dedong Li, Lei Bai, Rui Zhao

Unlike the existing cross-scale contrastive learning methods on graphs that only contrast a graph and its belonging nodes, the contrast between road segment and trajectory is elaborately tailored via novel positive sampling and adaptive weighting strategies.

Contrastive Learning Representation Learning

Uni6Dv2: Noise Elimination for 6D Pose Estimation

no code implementations15 Aug 2022 Mingshan Sun, Ye Zheng, Tianpeng Bao, Jianqiu Chen, Guoqiang Jin, Liwei Wu, Rui Zhao, Xiaoke Jiang

Uni6D is the first 6D pose estimation approach to employ a unified backbone network to extract features from both RGB and depth images.

6D Pose Estimation Denoising +2

Counterfactual Intervention Feature Transfer for Visible-Infrared Person Re-identification

no code implementations1 Aug 2022 Xulin Li, Yan Lu, Bin Liu, Yating Liu, Guojun Yin, Qi Chu, Jinyang Huang, Feng Zhu, Rui Zhao, Nenghai Yu

But we find existing graph-based methods in the visible-infrared person re-identification task (VI-ReID) suffer from bad generalization because of two issues: 1) train-test modality balance gap, which is a property of VI-ReID task.

Person Re-Identification

Auto-Encoding Adversarial Imitation Learning

no code implementations22 Jun 2022 Kaifeng Zhang, Rui Zhao, Ziming Zhang, Yang Gao

In this work, we propose Auto-Encoding Adversarial Imitation Learning (AEAIL), a robust and scalable AIL framework.

Imitation Learning Reinforcement Learning (RL)

Domain Invariant Masked Autoencoders for Self-supervised Learning from Multi-domains

no code implementations10 May 2022 Haiyang Yang, Meilin Chen, Yizhou Wang, Shixiang Tang, Feng Zhu, Lei Bai, Rui Zhao, Wanli Ouyang

While recent self-supervised learning methods have achieved good performances with evaluation set on the same domain as the training set, they will have an undesirable performance decrease when tested on a different domain.

Self-Supervised Learning

Uni6D: A Unified CNN Framework without Projection Breakdown for 6D Pose Estimation

no code implementations CVPR 2022 Xiaoke Jiang, Donghai Li, Hao Chen, Ye Zheng, Rui Zhao, Liwei Wu

They use a 2D CNN for RGB images and a per-pixel point cloud network for depth data, as well as a fusion network for feature fusion.

6D Pose Estimation

UniVIP: A Unified Framework for Self-Supervised Visual Pre-training

no code implementations CVPR 2022 Zhaowen Li, Yousong Zhu, Fan Yang, Wei Li, Chaoyang Zhao, Yingying Chen, Zhiyang Chen, Jiahao Xie, Liwei Wu, Rui Zhao, Ming Tang, Jinqiao Wang

Furthermore, our method can also exploit single-centric-object dataset such as ImageNet and outperforms BYOL by 2. 5% with the same pre-training epochs in linear probing, and surpass current self-supervised object detection methods on COCO dataset, demonstrating its universality and potential.

Image Classification object-detection +3

Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels

1 code implementation CVPR 2022 Yuchao Wang, Haochen Wang, Yujun Shen, Jingjing Fei, Wei Li, Guoqiang Jin, Liwei Wu, Rui Zhao, Xinyi Le

A common practice is to select the highly confident predictions as the pseudo ground-truth, but it leads to a problem that most pixels may be left unused due to their unreliability.

Semi-Supervised Semantic Segmentation

Maximum Entropy Population-Based Training for Zero-Shot Human-AI Coordination

1 code implementation22 Dec 2021 Rui Zhao, Jinming Song, Yufeng Yuan, Hu Haifeng, Yang Gao, Yi Wu, Zhongqian Sun, Yang Wei

We study the problem of training a Reinforcement Learning (RL) agent that is collaborative with humans without using any human data.

Reinforcement Learning (RL)

Feature Erasing and Diffusion Network for Occluded Person Re-Identification

1 code implementation CVPR 2022 Zhikang Wang, Feng Zhu, Shixiang Tang, Rui Zhao, Lihuo He, Jiangning Song

With the guidance of the occlusion scores from OEM, the feature diffusion process is mainly conducted on visible body parts, which guarantees the quality of the synthesized NTP characteristics.

 Ranked #1 on Person Re-Identification on Occluded REID (Rank-1 metric)

Person Re-Identification

FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing Flows

3 code implementations15 Nov 2021 Jiawei Yu, Ye Zheng, Xiang Wang, Wei Li, Yushuang Wu, Rui Zhao, Liwei Wu

However, current methods can not effectively map image features to a tractable base distribution and ignore the relationship between local and global features which are important to identify anomalies.

Ranked #6 on Anomaly Detection on MVTec AD (using extra training data)

Unsupervised Anomaly Detection Weakly Supervised Defect Detection

Boundary Distribution Estimation to Precise Object Detection

no code implementations2 Nov 2021 Haoran Zhou, Hang Huang, Rui Zhao, Wei Wang, Qingguo Zhou

In principal modern detectors, the task of object localization is implemented by the box subnet which concentrates on bounding box regression.

object-detection Object Detection +2

Focus Your Distribution: Coarse-to-Fine Non-Contrastive Learning for Anomaly Detection and Localization

no code implementations9 Oct 2021 Ye Zheng, Xiang Wang, Rui Deng, Tianpeng Bao, Rui Zhao, Liwei Wu

To facilitate the learning with only normal images, we propose a new pretext task called non-contrastive learning for the fine alignment stage.

Ranked #27 on Anomaly Detection on MVTec AD (using extra training data)

Contrastive Learning Unsupervised Anomaly Detection

Optical Flow Estimation for Spiking Camera

1 code implementation CVPR 2022 Liwen Hu, Rui Zhao, Ziluo Ding, Lei Ma, Boxin Shi, Ruiqin Xiong, Tiejun Huang

Further, for training SCFlow, we synthesize two sets of optical flow data for the spiking camera, SPIkingly Flying Things and Photo-realistic High-speed Motion, denoted as SPIFT and PHM respectively, corresponding to random high-speed and well-designed scenes.

Event-based vision Motion Estimation +1

Dr.Aid: Supporting Data-governance Rule Compliance for Decentralized Collaboration in an Automated Way

no code implementations3 Oct 2021 Rui Zhao, Malcolm Atkinson, Petros Papapanagiotou, Federica Magnoni, Jacques Fleuriot

It depends on federations sharing data that often have governance rules or external regulations restricting their use.


no code implementations29 Sep 2021 Shaobo Lin, Xingyu Zeng, Rui Zhao

Conventional training of deep neural networks usually requires a substantial amount of data with expensive human annotations.

Few-Shot Image Classification Few-Shot Learning +2

Zero-CL: Instance and Feature decorrelation for negative-free symmetric contrastive learning

no code implementations ICLR 2022 Shaofeng Zhang, Feng Zhu, Junchi Yan, Rui Zhao, Xiaokang Yang

The proposed two methods (FCL, ICL) can be combined synthetically, called Zero-CL, where ``Zero'' means negative samples are \textbf{zero} relevant, which allows Zero-CL to completely discard negative pairs i. e., with \textbf{zero} negative samples.

Contrastive Learning

Auto-Encoding Inverse Reinforcement Learning

no code implementations29 Sep 2021 Kaifeng Zhang, Rui Zhao, Ziming Zhang, Yang Gao

Reinforcement learning (RL) provides a powerful framework for decision-making, but its application in practice often requires a carefully designed reward function.

Imitation Learning reinforcement-learning +1

Multi-Source Video Domain Adaptation with Temporal Attentive Moment Alignment

no code implementations21 Sep 2021 Yuecong Xu, Jianfei Yang, Haozhi Cao, Keyu Wu, Min Wu, Rui Zhao, Zhenghua Chen

Multi-Source Domain Adaptation (MSDA) is a more practical domain adaptation scenario in real-world scenarios.

Unsupervised Domain Adaptation

Spatio-Temporal Recurrent Networks for Event-Based Optical Flow Estimation

1 code implementation10 Sep 2021 Ziluo Ding, Rui Zhao, Jiyuan Zhang, Tianxiao Gao, Ruiqin Xiong, Zhaofei Yu, Tiejun Huang

Recently, many deep learning methods have shown great success in providing promising solutions to many event-based problems, such as optical flow estimation.

Event-based Optical Flow Optical Flow Estimation +1

An Automated Framework for Supporting Data-Governance Rule Compliance in Decentralized MIMO Contexts

no code implementations2 Sep 2021 Rui Zhao

We propose Dr. Aid, a logic-based AI framework for automated compliance checking of data governance rules over data-flow graphs.

MST: Masked Self-Supervised Transformer for Visual Representation

no code implementations NeurIPS 2021 Zhaowen Li, Zhiyang Chen, Fan Yang, Wei Li, Yousong Zhu, Chaoyang Zhao, Rui Deng, Liwei Wu, Rui Zhao, Ming Tang, Jinqiao Wang

More importantly, the masked tokens together with the remaining tokens are further recovered by a global image decoder, which preserves the spatial information of the image and is more friendly to the downstream dense prediction tasks.

Language Modelling Masked Language Modeling +3

Improving Facial Attribute Recognition by Group and Graph Learning

no code implementations28 May 2021 Zhenghao Chen, Shuhang Gu, Feng Zhu, Jing Xu, Rui Zhao

For the spatial correlation, we aggregate attributes with spatial similarity into a part-based group and then introduce a Group Attention Learning to generate the group attention and the part-based group feature.

Graph Learning

Neighbourhood-guided Feature Reconstruction for Occluded Person Re-Identification

no code implementations16 May 2021 Shijie Yu, Dapeng Chen, Rui Zhao, Haobin Chen, Yu Qiao

Person images captured by surveillance cameras are often occluded by various obstacles, which lead to defective feature representation and harm person re-identification (Re-ID) performance.

Person Re-Identification

On Addressing Practical Challenges for RNN-Transducer

no code implementations27 Apr 2021 Rui Zhao, Jian Xue, Jinyu Li, Wenning Wei, Lei He, Yifan Gong

The first challenge is solved with a splicing data method which concatenates the speech segments extracted from the source domain data.

speech-recognition Speech Recognition

Memory Enhanced Embedding Learning for Cross-Modal Video-Text Retrieval

no code implementations29 Mar 2021 Rui Zhao, Kecheng Zheng, Zheng-Jun Zha, Hongtao Xie, Jiebo Luo

The cross-modal memory module is employed to record the instance embeddings of all the datasets for global negative mining.

Retrieval Text Retrieval +1

Mutual Information State Intrinsic Control

2 code implementations ICLR 2021 Rui Zhao, Yang Gao, Pieter Abbeel, Volker Tresp, Wei Xu

Reinforcement learning has been shown to be highly successful at many challenging tasks.

Progressive Correspondence Pruning by Consensus Learning

no code implementations ICCV 2021 Chen Zhao, Yixiao Ge, Feng Zhu, Rui Zhao, Hongsheng Li, Mathieu Salzmann

Correspondence selection aims to correctly select the consistent matches (inliers) from an initial set of putative correspondences.

Denoising Pose Estimation +1

Internal Language Model Estimation for Domain-Adaptive End-to-End Speech Recognition

no code implementations3 Nov 2020 Zhong Meng, Sarangarajan Parthasarathy, Eric Sun, Yashesh Gaur, Naoyuki Kanda, Liang Lu, Xie Chen, Rui Zhao, Jinyu Li, Yifan Gong

The external language models (LM) integration remains a challenging task for end-to-end (E2E) automatic speech recognition (ASR) which has no clear division between acoustic and language models.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +2

The Vulnerability of the Neural Networks Against Adversarial Examples in Deep Learning Algorithms

no code implementations2 Nov 2020 Rui Zhao

Based on current security threats faced by deep learning, this paper introduces the problem of adversarial examples in deep learning, sorts out the existing attack and defense methods of the black box and white box, and classifies them.

Enhancing and Learning Denoiser without Clean Reference

no code implementations9 Sep 2020 Rui Zhao, Daniel P. K. Lun, Kin-Man Lam

Recent studies on learning-based image denoising have achieved promising performance on various noise reduction tasks.

Image Denoising

Transfer Learning Approaches for Streaming End-to-End Speech Recognition System

no code implementations12 Aug 2020 Vikas Joshi, Rui Zhao, Rupesh R. Mehta, Kshitiz Kumar, Jinyu Li

Transfer learning (TL) is widely used in conventional hybrid automatic speech recognition (ASR) system, to transfer the knowledge from source to target language.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +2

Deep Reinforcement Learning Based Mobile Edge Computing for Intelligent Internet of Things

no code implementations1 Aug 2020 Rui Zhao, Xinjie Wang, Junjuan Xia, Liseng Fan

In particular, the system cost of latency and energy consumption can be reduced significantly by the proposed deep reinforcement learning based algorithm.

Edge-computing reinforcement-learning +1

Developing RNN-T Models Surpassing High-Performance Hybrid Models with Customization Capability

no code implementations30 Jul 2020 Jinyu Li, Rui Zhao, Zhong Meng, Yanqing Liu, Wenning Wei, Sarangarajan Parthasarathy, Vadim Mazalov, Zhenghao Wang, Lei He, Sheng Zhao, Yifan Gong

Because of its streaming nature, recurrent neural network transducer (RNN-T) is a very promising end-to-end (E2E) model that may replace the popular hybrid model for automatic speech recognition.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

Learning Individualized Treatment Rules with Estimated Translated Inverse Propensity Score

1 code implementation2 Jul 2020 Zhiliang Wu, Yinchong Yang, Yunpu Ma, Yushan Liu, Rui Zhao, Michael Moor, Volker Tresp

Randomized controlled trials typically analyze the effectiveness of treatments with the goal of making treatment recommendations for patient subgroups.

Enhancement of a CNN-Based Denoiser Based on Spatial and Spectral Analysis

no code implementations28 Jun 2020 Rui Zhao, Kin-Man Lam, Daniel P. K. Lun

Since most of the content or energy of natural images resides in the low-frequency spectrum, their transformed coefficients in the frequency domain are highly imbalanced.

Image Denoising

Continual Representation Learning for Biometric Identification

1 code implementation8 Jun 2020 Bo Zhao, Shixiang Tang, Dapeng Chen, Hakan Bilen, Rui Zhao

With the explosion of digital data in recent years, continuously learning new tasks from a stream of data without forgetting previously acquired knowledge has become increasingly important.

Continual Learning Knowledge Distillation +1

Self-supervising Fine-grained Region Similarities for Large-scale Image Localization

3 code implementations ECCV 2020 Yixiao Ge, Haibo Wang, Feng Zhu, Rui Zhao, Hongsheng Li

The task of large-scale retrieval-based image localization is to estimate the geographical location of a query image by recognizing its nearest reference images from a city-scale dataset.

Image Retrieval Retrieval

Bayesian Adversarial Human Motion Synthesis

1 code implementation CVPR 2020 Rui Zhao, Hui Su, Qiang Ji

By explicitly capturing the distribution of the data and parameters, our model has a more compact parameterization compared to GAN-based generative models.

Bayesian Inference Data Augmentation +1

COCAS: A Large-Scale Clothes Changing Person Dataset for Re-identification

no code implementations CVPR 2020 Shijie Yu, Shihua Li, Dapeng Chen, Rui Zhao, Junjie Yan, Yu Qiao

To address the clothes changing person re-id problem, we construct a novel large-scale re-id benchmark named ClOthes ChAnging Person Set (COCAS), which provides multiple images of the same identity with different clothes.

Person Re-Identification

Exploring Pre-training with Alignments for RNN Transducer based End-to-End Speech Recognition

no code implementations1 May 2020 Hu Hu, Rui Zhao, Jinyu Li, Liang Lu, Yifan Gong

Recently, the recurrent neural network transducer (RNN-T) architecture has become an emerging trend in end-to-end automatic speech recognition research due to its advantages of being capable for online streaming speech recognition.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +2

Stacked Convolutional Deep Encoding Network for Video-Text Retrieval

no code implementations10 Apr 2020 Rui Zhao, Kecheng Zheng, Zheng-Jun Zha

Existing dominant approaches for cross-modal video-text retrieval task are to learn a joint embedding space to measure the cross-modal similarity.

Language Modelling Retrieval +2

Learning to Cluster Faces via Confidence and Connectivity Estimation

3 code implementations CVPR 2020 Lei Yang, Dapeng Chen, Xiaohang Zhan, Rui Zhao, Chen Change Loy, Dahua Lin

With the vertex confidence and edge connectivity, we can naturally organize more relevant vertices on the affinity graph and group them into clusters.

Connectivity Estimation Face Clustering +1

High-Accuracy and Low-Latency Speech Recognition with Two-Head Contextual Layer Trajectory LSTM Model

no code implementations17 Mar 2020 Jinyu Li, Rui Zhao, Eric Sun, Jeremy H. M. Wong, Amit Das, Zhong Meng, Yifan Gong

While the community keeps promoting end-to-end models over conventional hybrid models, which usually are long short-term memory (LSTM) models trained with a cross entropy criterion followed by a sequence discriminative training criterion, we argue that such conventional hybrid models can still be significantly improved.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

Structured Domain Adaptation with Online Relation Regularization for Unsupervised Person Re-ID

4 code implementations14 Mar 2020 Yixiao Ge, Feng Zhu, Dapeng Chen, Rui Zhao, Xiaogang Wang, Hongsheng Li

To tackle the challenges, we propose an end-to-end structured domain adaptation framework with an online relation-consistency regularization term.

Pseudo Label Translation +2

Towards a computer-interpretable actionable formal model to encode data governance rules

no code implementations19 Nov 2019 Rui Zhao, Malcolm Atkinson

With the needs of science and business, data sharing and re-use has become an intensive activity for various areas.

Bayesian Graph Convolution LSTM for Skeleton Based Action Recognition

no code implementations ICCV 2019 Rui Zhao, Kang Wang, Hui Su, Qiang Ji

Finally, the whole model is extended under the Bayesian framework to a probabilistic model in order to better capture the stochasticity and variation in the data.

Action Recognition Anatomy +2

Self-Supervised State-Control through Intrinsic Mutual Information Rewards

1 code implementation25 Sep 2019 Rui Zhao, Volker Tresp, Wei Xu

Our results show that the mutual information between the context states and the states of interest can be an effective ingredient for overcoming challenges in robotic manipulation tasks with sparse rewards.

OpenAI Gym reinforcement-learning +1

Maximum Entropy-Regularized Multi-Goal Reinforcement Learning

3 code implementations21 May 2019 Rui Zhao, Xudong Sun, Volker Tresp

This objective encourages the agent to maximize the expected return, as well as to achieve more diverse goals.

Multi-Goal Reinforcement Learning OpenAI Gym +2

Neural Networks for Modeling Source Code Edits

no code implementations4 Apr 2019 Rui Zhao, David Bieber, Kevin Swersky, Daniel Tarlow

In this work, we instead treat source code as a dynamic object and tackle the problem of modeling the edits that software developers make to source code files.

Curiosity-Driven Experience Prioritization via Density Estimation

no code implementations20 Feb 2019 Rui Zhao, Volker Tresp

In Reinforcement Learning (RL), an agent explores the environment and collects trajectories into the memory buffer for later learning.

Density Estimation OpenAI Gym +3

Advancing Acoustic-to-Word CTC Model with Attention and Mixed-Units

no code implementations31 Dec 2018 Amit Das, Jinyu Li, Guoli Ye, Rui Zhao, Yifan Gong

In particular, we introduce Attention CTC, Self-Attention CTC, Hybrid CTC, and Mixed-unit CTC.

Language Modelling

Efficient Dialog Policy Learning via Positive Memory Retention

2 code implementations2 Oct 2018 Rui Zhao, Volker Tresp

This paper is concerned with the training of recurrent neural networks as goal-oriented dialog agents using reinforcement learning.

Goal-Oriented Dialog Object Discovery +1

Energy-Based Hindsight Experience Prioritization

2 code implementations2 Oct 2018 Rui Zhao, Volker Tresp

We evaluate our Energy-Based Prioritization (EBP) approach on four challenging robotic manipulation tasks in simulation.

reinforcement-learning Reinforcement Learning (RL)

Learning Goal-Oriented Visual Dialog via Tempered Policy Gradient

1 code implementation2 Jul 2018 Rui Zhao, Volker Tresp

Learning goal-oriented dialogues by means of deep reinforcement learning has recently become a popular research topic.

Policy Gradient Methods Reinforcement Learning (RL) +1

Bilateral Ordinal Relevance Multi-Instance Regression for Facial Action Unit Intensity Estimation

no code implementations CVPR 2018 Yong Zhang, Rui Zhao, Wei-Ming Dong, Bao-Gang Hu, Qiang Ji

The majority of methods directly apply supervised learning techniques to AU intensity estimation while few methods exploit unlabeled samples to improve the performance.


Developing Far-Field Speaker System Via Teacher-Student Learning

no code implementations14 Apr 2018 Jinyu Li, Rui Zhao, Zhuo Chen, Changliang Liu, Xiong Xiao, Guoli Ye, Yifan Gong

In this study, we develop the keyword spotting (KWS) and acoustic model (AM) components in a far-field speaker system.

Keyword Spotting Model Compression

Advancing Connectionist Temporal Classification With Attention Modeling

no code implementations15 Mar 2018 Amit Das, Jinyu Li, Rui Zhao, Yifan Gong

In this study, we propose advancing all-neural speech recognition by directly incorporating attention modeling within the Connectionist Temporal Classification (CTC) framework.

Classification General Classification +3

Advancing Acoustic-to-Word CTC Model

no code implementations15 Mar 2018 Jinyu Li, Guoli Ye, Amit Das, Rui Zhao, Yifan Gong

However, the word-based CTC model suffers from the out-of-vocabulary (OOV) issue as it can only model limited number of words in the output layer and maps all the remaining words into an OOV output node.

Language Modelling

Acoustic-To-Word Model Without OOV

no code implementations28 Nov 2017 Jinyu Li, Guoli Ye, Rui Zhao, Jasha Droppo, Yifan Gong

However, this type of word-based CTC model suffers from the out-of-vocabulary (OOV) issue as it can only model limited number of words in the output layer and maps all the remaining words into an OOV output node.

Improved training for online end-to-end speech recognition systems

1 code implementation6 Nov 2017 Suyoun Kim, Michael L. Seltzer, Jinyu Li, Rui Zhao

Achieving high accuracy with end-to-end speech recognizers requires careful parameter initialization prior to training.

speech-recognition Speech Recognition

Large-Scale Domain Adaptation via Teacher-Student Learning

no code implementations17 Aug 2017 Jinyu Li, Michael L. Seltzer, Xi Wang, Rui Zhao, Yifan Gong

High accuracy speech recognition requires a large amount of transcribed data for supervised training.

Domain Adaptation speech-recognition +1

A Nuclear-norm Model for Multi-Frame Super-Resolution Reconstruction from Video Clips

no code implementations17 Apr 2017 Rui Zhao, Raymond H. Chan

Then a low-rank model is used to construct the reference frame in high-resolution by incorporating the information of the low-resolution frames.

Multi-Frame Super-Resolution Optical Flow Estimation

Two-Stream RNN/CNN for Action Recognition in 3D Videos

no code implementations22 Mar 2017 Rui Zhao, Haider Ali, Patrick van der Smagt

The recognition of actions from video sequences has many applications in health monitoring, assisted living, surveillance, and smart homes.

Action Recognition Temporal Action Localization

Deep Learning and Its Applications to Machine Health Monitoring: A Survey

1 code implementation16 Dec 2016 Rui Zhao, Ruqiang Yan, Zhenghua Chen, Kezhi Mao, Peng Wang, Robert X. Gao

Since 2006, deep learning (DL) has become a rapidly growing research direction, redefining state-of-the-art performances in a wide range of areas such as object recognition, image segmentation, speech recognition and machine translation.

Image Segmentation Machine Translation +5

Saliency Detection by Multi-Context Deep Learning

no code implementations CVPR 2015 Rui Zhao, Wanli Ouyang, Hongsheng Li, Xiaogang Wang

Low-level saliency cues or priors do not produce good enough saliency detection results especially when the salient object presents in a low-contrast background with confusing visual appearance.

Image Classification object-detection +3

Highly Efficient Forward and Backward Propagation of Convolutional Neural Networks for Pixelwise Classification

no code implementations15 Dec 2014 Hongsheng Li, Rui Zhao, Xiaogang Wang

The proposed algorithms eliminate all the redundant computation in convolution and pooling on images by introducing novel d-regularly sparse kernels.

Classification General Classification +5

Nilpotent matrices having a given Jordan type as maximum commuting nilpotent orbit

1 code implementation8 Sep 2014 Anthony Iarrobino, Leila Khatami, Bart Van Steirteghem, Rui Zhao

In 2012 P. Oblak formulated a conjecture concerning the cardinality of the set of partitions $P$ such that ${\mathcal Q}(P)$ is a given stable partition $ Q$ with two parts, and proved some special cases.

Rings and Algebras Commutative Algebra Representation Theory 15A27 (Primary), 05E40 (Secondary), 13E10, 15A21

Learning Mid-level Filters for Person Re-identification

no code implementations CVPR 2014 Rui Zhao, Wanli Ouyang, Xiaogang Wang

In this paper, we propose a novel approach of learning mid-level filters from automatically discovered patch clusters for person re-identification.

Patch Matching Person Re-Identification

DeepReID: Deep Filter Pairing Neural Network for Person Re-Identification

no code implementations CVPR 2014 Wei Li, Rui Zhao, Tong Xiao, Xiaogang Wang

In this paper, we propose a novel filter pairing neural network (FPNN) to jointly handle misalignment, photometric and geometric transforms, occlusions and background clutter.

Person Re-Identification

Unsupervised Salience Learning for Person Re-identification

no code implementations CVPR 2013 Rui Zhao, Wanli Ouyang, Xiaogang Wang

In this paper, we propose a novel perspective for person re-identification based on unsupervised salience learning.

Patch Matching Person Re-Identification

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