Search Results for author: Dong Xu

Found 61 papers, 14 papers with code

SRDAN: Scale-Aware and Range-Aware Domain Adaptation Network for Cross-Dataset 3D Object Detection

no code implementations CVPR 2021 Weichen Zhang, Wen Li, Dong Xu

In this work, we propose a new cross-dataset 3D object detection method named Scale-aware and Range-aware Domain Adaptation Network (SRDAN).

3D Object Detection Domain Adaptation

CBANet: Towards Complexity and Bitrate Adaptive Deep Image Compression using a Single Network

no code implementations26 May 2021 Jinyang Guo, Dong Xu, Guo Lu

Furthermore, to achieve variable bitrate decoding with one single decoder, we propose a bitrate adaptive module to project the representation from a base bitrate to the expected representation at a target bitrate for transmission.

Image Compression

FVC: A New Framework towards Deep Video Compression in Feature Space

no code implementations CVPR 2021 Zhihao Hu, Guo Lu, Dong Xu

In this work, we propose a feature-space video coding network (FVC) by performing all major operations (i. e., motion estimation, motion compression, motion compensation and residual compression) in the feature space.

Motion Compensation Motion Estimation +1

VoxelContext-Net: An Octree based Framework for Point Cloud Compression

no code implementations CVPR 2021 Zizheng Que, Guo Lu, Dong Xu

In this paper, we propose a two-stage deep learning framework called VoxelContext-Net for both static and dynamic point cloud compression.

Back-tracing Representative Points for Voting-based 3D Object Detection in Point Clouds

1 code implementation CVPR 2021 Bowen Cheng, Lu Sheng, Shaoshuai Shi, Ming Yang, Dong Xu

Inspired by the back-tracing strategy in the conventional Hough voting methods, in this work, we introduce a new 3D object detection method, named as Back-tracing Representative Points Network (BRNet), which generatively back-traces the representative points from the vote centers and also revisits complementary seed points around these generated points, so as to better capture the fine local structural features surrounding the potential objects from the raw point clouds.

3D Object Detection

VDM-DA: Virtual Domain Modeling for Source Data-free Domain Adaptation

no code implementations26 Mar 2021 Jiayi Tian, Jing Zhang, Wen Li, Dong Xu

On the other hand, we also design an effective distribution alignment method to reduce the distribution divergence between the virtual domain and the target domain by gradually improving the compactness of the target domain distribution through model learning.

Object Recognition Unsupervised Domain Adaptation

Salient Object Detection via Integrity Learning

3 code implementations19 Jan 2021 Mingchen Zhuge, Deng-Ping Fan, Nian Liu, Dingwen Zhang, Dong Xu, Ling Shao

2) Based on the DFA features, we introduce the integrity channel enhancement (ICE) component with the goal of enhancing feature channels that highlight the integral salient objects at the macro level, while suppressing the other distracting ones.

Object Detection Salient Object Detection

StyleFormer: Real-Time Arbitrary Style Transfer via Parametric Style Composition

no code implementations ICCV 2021 Xiaolei Wu, Zhihao Hu, Lu Sheng, Dong Xu

In this work, we propose a new feed-forward arbitrary style transfer method, referred to as StyleFormer, which can simultaneously fulfill fine-grained style diversity and semantic content coherency.

Style Transfer

STVGBert: A Visual-Linguistic Transformer Based Framework for Spatio-Temporal Video Grounding

no code implementations ICCV 2021 Rui Su, Qian Yu, Dong Xu

Spatio-temporal video grounding (STVG) aims to localize a spatio-temporal tube of a target object in an untrimmed video based on a query sentence.

3DVG-Transformer: Relation Modeling for Visual Grounding on Point Clouds

no code implementations ICCV 2021 Lichen Zhao, Daigang Cai, Lu Sheng, Dong Xu

Visual grounding on 3D point clouds is an emerging vision and language task that benefits various applications in understanding the 3D visual world.

Object Proposal Generation Visual Grounding

Formal Language Constrained Markov Decision Processes

no code implementations1 Jan 2021 Eleanor Quint, Dong Xu, Samuel W Flint, Stephen D Scott, Matthew Dwyer

In order to satisfy safety conditions, an agent may be constrained from acting freely.

Inception Convolution with Efficient Dilation Search

1 code implementation CVPR 2021 Jie Liu, Chuming Li, Feng Liang, Chen Lin, Ming Sun, Junjie Yan, Wanli Ouyang, Dong Xu

To develop a practical method for learning complex inception convolution based on the data, a simple but effective search algorithm, referred to as efficient dilation optimization (EDO), is developed.

Human Detection Instance Segmentation +3

Human-centric Spatio-Temporal Video Grounding With Visual Transformers

1 code implementation10 Nov 2020 Zongheng Tang, Yue Liao, Si Liu, Guanbin Li, Xiaojie Jin, Hongxu Jiang, Qian Yu, Dong Xu

HC-STVG is a video grounding task that requires both spatial (where) and temporal (when) localization.

Temporal Localization

Deep Learning Analysis and Age Prediction from Shoeprints

1 code implementation7 Nov 2020 Muhammad Hassan, Yan Wang, Di Wang, Daixi Li, Yanchun Liang, You Zhou, Dong Xu

We collected 100, 000 shoeprints of subjects ranging from 7 to 80 years old and used the data to develop a deep learning end-to-end model ShoeNet to analyze age-related patterns and predict age.

A Method of Generating Measurable Panoramic Image for Indoor Mobile Measurement System

no code implementations27 Oct 2020 Hao Ma, Jingbin Liu, Zhirong Hu, Hongyu Qiu, Dong Xu, Zemin Wang, Xiaodong Gong, Sheng Yang

This paper designs a technique route to generate high-quality panoramic image with depth information, which involves two critical research hotspots: fusion of LiDAR and image data and image stitching.

Image Stitching

Improving Deep Video Compression by Resolution-adaptive Flow Coding

no code implementations ECCV 2020 Zhihao Hu, Zhenghao Chen, Dong Xu, Guo Lu, Wanli Ouyang, Shuhang Gu

In this work, we propose a new framework called Resolution-adaptive Flow Coding (RaFC) to effectively compress the flow maps globally and locally, in which we use multi-resolution representations instead of single-resolution representations for both the input flow maps and the output motion features of the MV encoder.

Optical Flow Estimation Video Compression

Systematic Generation of Diverse Benchmarks for DNN Verification

1 code implementation14 Jul 2020 Dong Xu, David Shriver, Matthew B. Dwyer, Sebastian Elbaum

The field of verification has advanced due to the interplay of theoretical development and empirical evaluation.

Simulating multi-exit evacuation using deep reinforcement learning

no code implementations11 Jul 2020 Dong Xu, Xiao Huang, Joseph Mango, Xiang Li, Zhenlong Li

We propose a multi-exit evacuation simulation based on Deep Reinforcement Learning (DRL), referred to as the MultiExit-DRL, which involves in a Deep Neural Network (DNN) framework to facilitate state-to-action mapping.

Enhance Curvature Information by Structured Stochastic Quasi-Newton Methods

no code implementations CVPR 2021 Ming-Han Yang, Dong Xu, Hongyu Chen, Zaiwen Wen, Mengyun Chen

In this paper, we consider stochastic second-order methods for minimizing a finite summation of nonconvex functions.

Sketchy Empirical Natural Gradient Methods for Deep Learning

no code implementations10 Jun 2020 Ming-Han Yang, Dong Xu, Zaiwen Wen, Mengyun Chen, Pengxiang Xu

Experiments on the distributed large-batch training show that the scaling efficiency is quite reasonable.

Content Adaptive and Error Propagation Aware Deep Video Compression

no code implementations ECCV 2020 Guo Lu, Chunlei Cai, Xiaoyun Zhang, Li Chen, Wanli Ouyang, Dong Xu, Zhiyong Gao

Therefore, the encoder is adaptive to different video contents and achieves better compression performance by reducing the domain gap between the training and testing datasets.

Video Compression

Channel Pruning Guided by Classification Loss and Feature Importance

no code implementations15 Mar 2020 Jinyang Guo, Wanli Ouyang, Dong Xu

To this end, we propose a new strategy to suppress the influence of unimportant features (i. e., the features will be removed at the next pruning stage).

Classification Feature Importance +1

A Unified End-to-End Framework for Efficient Deep Image Compression

2 code implementations9 Feb 2020 Jiaheng Liu, Guo Lu, Zhihao Hu, Dong Xu

Our EDIC method can also be readily incorporated with the Deep Video Compression (DVC) framework to further improve the video compression performance.

Image Compression Video Compression

Translating multispectral imagery to nighttime imagery via conditional generative adversarial networks

no code implementations28 Dec 2019 Xiao Huang, Dong Xu, Zhenlong Li, Cuizhen Wang

The results of this study prove the possibility of multispectral-to-nighttime translation and further indicate that, with the additional social media data, the generated nighttime imagery can be very similar to the ground-truth imagery.

Translation

Formal Language Constraints for Markov Decision Processes

1 code implementation2 Oct 2019 Eleanor Quint, Dong Xu, Samuel Flint, Stephen Scott, Matthew Dwyer

In order to satisfy safety conditions, an agent may be constrained from acting freely.

Atari Games

IntersectGAN: Learning Domain Intersection for Generating Images with Multiple Attributes

no code implementations21 Sep 2019 Zehui Yao, Boyan Zhang, Zhiyong Wang, Wanli Ouyang, Dong Xu, Dagan Feng

For example, given two image domains $X_1$ and $X_2$ with certain attributes, the intersection $X_1 \cap X_2$ denotes a new domain where images possess the attributes from both $X_1$ and $X_2$ domains.

Refactoring Neural Networks for Verification

1 code implementation6 Aug 2019 David Shriver, Dong Xu, Sebastian Elbaum, Matthew B. Dwyer

Deep neural networks (DNN) are growing in capability and applicability.

Improving Action Localization by Progressive Cross-stream Cooperation

no code implementations CVPR 2019 Rui Su, Wanli Ouyang, Luping Zhou, Dong Xu

Specifically, we first generate a larger set of region proposals by combining the latest region proposals from both streams, from which we can readily obtain a larger set of labelled training samples to help learn better action detection models.

Action Classification Action Detection +2

Gated Group Self-Attention for Answer Selection

no code implementations26 May 2019 Dong Xu, Jianhui Ji, Haikuan Huang, Hongbo Deng, Wu-Jun Li

Nevertheless, it is difficult for RNN based models to capture the information about long-range dependency among words in the sentences of questions and answers.

Answer Selection Machine Translation +1

Hashing based Answer Selection

no code implementations26 May 2019 Dong Xu, Wu-Jun Li

HAS adopts a hashing strategy to learn a binary matrix representation for each answer, which can dramatically reduce the memory cost for storing the matrix representations of answers.

Answer Selection

DVC: An End-to-end Deep Video Compression Framework

5 code implementations CVPR 2019 Guo Lu, Wanli Ouyang, Dong Xu, Xiaoyun Zhang, Chunlei Cai, Zhiyong Gao

Conventional video compression approaches use the predictive coding architecture and encode the corresponding motion information and residual information.

MS-SSIM Optical Flow Estimation +2

Dividing and Aggregating Network for Multi-view Action Recognition

no code implementations ECCV 2018 Dongang Wang, Wanli Ouyang, Wen Li, Dong Xu

We then train view-specific action classifiers based on the view-specific representation for each view and a view classifier based on the shared representation at lower layers.

Action Recognition

Deep Kalman Filtering Network for Video Compression Artifact Reduction

1 code implementation ECCV 2018 Guo Lu, Wanli Ouyang, Dong Xu, Xiaoyun Zhang, Zhiyong Gao, Ming-Ting Sun

In this paper, we model the video artifact reduction task as a Kalman filtering procedure and restore decoded frames through a deep Kalman filtering network.

Video Compression

Collaborative and Adversarial Network for Unsupervised Domain Adaptation

1 code implementation CVPR 2018 Weichen Zhang, Wanli Ouyang, Wen Li, Dong Xu

In this paper, we propose a new unsupervised domain adaptation approach called Collaborative and Adversarial Network (CAN) through domain-collaborative and domain-adversarial training of neural networks.

Unsupervised Domain Adaptation

Complex Event Detection by Identifying Reliable Shots From Untrimmed Videos

no code implementations ICCV 2017 Hehe Fan, Xiaojun Chang, De Cheng, Yi Yang, Dong Xu, Alexander G. Hauptmann

relevant) to the given event class, we formulate this task as a multi-instance learning (MIL) problem by taking each video as a bag and the video shots in each video as instances.

Event Detection

MUFold-SS: Protein Secondary Structure Prediction Using Deep Inception-Inside-Inception Networks

no code implementations12 Sep 2017 Chao Fang, Yi Shang, Dong Xu

Results: Here, a very deep neural network, the deep inception-inside-inception networks (Deep3I), is proposed for protein secondary structure prediction and a software tool was implemented using this network.

Image Classification Protein Secondary Structure Prediction

Image Projective Invariants

no code implementations19 Jul 2017 Erbo Li, Hanlin Mo, Dong Xu, Hua Li

In this paper, we propose relative projective differential invariants (RPDIs) which are invariant to general projective transformations.

Image Retrieval

SPFTN: A Self-Paced Fine-Tuning Network for Segmenting Objects in Weakly Labelled Videos

no code implementations CVPR 2017 Dingwen Zhang, Le Yang, Deyu Meng, Dong Xu, Junwei Han

Object segmentation in weakly labelled videos is an interesting yet challenging task, which aims at learning to perform category-specific video object segmentation by only using video-level tags.

Semantic Segmentation Video Object Segmentation +1

Recent Advances in Transfer Learning for Cross-Dataset Visual Recognition: A Problem-Oriented Perspective

no code implementations11 May 2017 Jing Zhang, Wanqing Li, Philip Ogunbona, Dong Xu

This paper takes a problem-oriented perspective and presents a comprehensive review of transfer learning methods, both shallow and deep, for cross-dataset visual recognition.

Transfer Learning

Shape DNA: Basic Generating Functions for Geometric Moment Invariants

no code implementations7 Mar 2017 Erbo Li, Yazhou Huang, Dong Xu, Hua Li

Two fundamental building blocks or generating functions (GFs) for invariants are discovered, which are dot product and vector product of point vectors in Euclidean space.

Affine Transformation Information Retrieval

Learning Multi-level Deep Representations for Image Emotion Classification

no code implementations22 Nov 2016 Tianrong Rao, Min Xu, Dong Xu

The proposed MldrNet combines deep representations of different levels, i. e. image semantics, image aesthetics, and low-level visual features to effectively classify the emotion types of different kinds of images, such as abstract paintings and web images.

Classification Emotion Classification +1

A Siamese Long Short-Term Memory Architecture for Human Re-Identification

no code implementations European Conference on Computer Vision 2016 Rahul Rama Varior, Bing Shuai, Jiwen Lu, Dong Xu, Gang Wang

Matching pedestrians across multiple camera views known as human re-identification (re-identification) is a challenging problem in visual surveillance.

Person Re-Identification

Spatio-Temporal LSTM with Trust Gates for 3D Human Action Recognition

no code implementations24 Jul 2016 Jun Liu, Amir Shahroudy, Dong Xu, Gang Wang

To handle the noise and occlusion in 3D skeleton data, we introduce new gating mechanism within LSTM to learn the reliability of the sequential input data and accordingly adjust its effect on updating the long-term context information stored in the memory cell.

Action Analysis Skeleton Based Action Recognition

Full-Time Supervision based Bidirectional RNN for Factoid Question Answering

no code implementations19 Jun 2016 Dong Xu, Wu-Jun Li

Hence, these existing models don't put supervision (loss or similarity calculation) at every time step, which will lose some useful information.

Question Answering

Fast Algorithms for Linear and Kernel SVM+

no code implementations CVPR 2016 Wen Li, Dengxin Dai, Mingkui Tan, Dong Xu, Luc van Gool

The SVM+ approach has shown excellent performance in visual recognition tasks for exploiting privileged information in the training data.

Dimensionality-Dependent Generalization Bounds for $k$-Dimensional Coding Schemes

no code implementations3 Jan 2016 Tongliang Liu, DaCheng Tao, Dong Xu

Can we obtain dimensionality-dependent generalization bounds for $k$-dimensional coding schemes that are tighter than dimensionality-independent bounds when data is in a finite-dimensional feature space?

Dictionary Learning Generalization Bounds +1

Multi-View Domain Generalization for Visual Recognition

no code implementations ICCV 2015 Li Niu, Wen Li, Dong Xu

Considering the recent works show the domain generalization capability can be enhanced by fusing multiple SVM classifiers, we build upon exemplar SVMs to learn a set of SVM classifiers by using one positive sample and all negative samples in the source domain each time.

Domain Generalization

FaLRR: A Fast Low Rank Representation Solver

no code implementations CVPR 2015 Shijie Xiao, Wen Li, Dong Xu, DaCheng Tao

In this paper, we develop a fast LRR solver called FaLRR, by reformulating LRR as a new optimization problem with regard to factorized data (which is obtained by skinny SVD of the original data matrix).

Face Clustering

Object-Based RGBD Image Co-Segmentation With Mutex Constraint

no code implementations CVPR 2015 Huazhu Fu, Dong Xu, Stephen Lin, Jiang Liu

We present an object-based co-segmentation method that takes advantage of depth data and is able to correctly handle noisy images in which the common foreground object is missing.

Visual Recognition by Learning From Web Data: A Weakly Supervised Domain Generalization Approach

no code implementations CVPR 2015 Li Niu, Wen Li, Dong Xu

In this work, we formulate a new weakly supervised domain generalization problem for the visual recognition task by using loosely labeled web images/videos as training data.

Domain Generalization

Scalable Nuclear-norm Minimization by Subspace Pursuit Proximal Riemannian Gradient

no code implementations10 Mar 2015 Mingkui Tan, Shijie Xiao, Junbin Gao, Dong Xu, Anton Van Den Hengel, Qinfeng Shi

Nuclear-norm regularization plays a vital role in many learning tasks, such as low-rank matrix recovery (MR), and low-rank representation (LRR).

Matrix Completion

Recognizing RGB Images by Learning from RGB-D Data

no code implementations CVPR 2014 Lin Chen, Wen Li, Dong Xu

In this work, we propose a new framework for recognizing RGB images captured by the conventional cameras by leveraging a set of labeled RGB-D data, in which the depth features can be additionally extracted from the depth images.

Object Recognition Unsupervised Domain Adaptation

Object-based Multiple Foreground Video Co-segmentation

no code implementations CVPR 2014 Huazhu Fu, Dong Xu, Bao Zhang, Stephen Lin

We present a video co-segmentation method that uses category-independent object proposals as its basic element and can extract multiple foreground objects in a video set.

Learning by Associating Ambiguously Labeled Images

no code implementations CVPR 2013 Zinan Zeng, Shijie Xiao, Kui Jia, Tsung-Han Chan, Shenghua Gao, Dong Xu, Yi Ma

Our framework is motivated by the observation that samples from the same class repetitively appear in the collection of ambiguously labeled training images, while they are just ambiguously labeled in each image.

Event Recognition in Videos by Learning from Heterogeneous Web Sources

no code implementations CVPR 2013 Lin Chen, Lixin Duan, Dong Xu

In this work, we propose to leverage a large number of loosely labeled web videos (e. g., from YouTube) and web images (e. g., from Google/Bing image search) for visual event recognition in consumer videos without requiring any labeled consumer videos.

Domain Adaptation Image Retrieval

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