64 citations · 272 across the 27 of their papers we have counts for
27 papers
Dense Video Captioning using Graph-based Sentence Summarization
Zhiwang Zhang, Dong Xu, Wanli Ouyang +1
Recently, dense video captioning has made attractive progress in detecting and captioning all events in a long untrimmed video. Despite promising results were achieved, most existi…
Progressive Modality Cooperation for Multi-Modality Domain Adaptation
Weichen Zhang, Dong Xu, Jing Zhang +1
In this work, we propose a new generic multi-modality domain adaptation framework called Progressive Modality Cooperation (PMC) to transfer the knowledge learned from the source do…
Self-Paced Collaborative and Adversarial Network for Unsupervised Domain Adaptation
Weichen Zhang, Dong Xu, Wanli Ouyang +1
This paper proposes a new unsupervised domain adaptation approach called Collaborative and Adversarial Network (CAN), which uses the domain-collaborative and domain-adversarial lea…
Improving Weakly Supervised Temporal Action Localization by Exploiting Multi-resolution Information in Temporal Domain
Rui Su, Dong Xu, Luping Zhou +1
Weakly supervised temporal action localization is a challenging task as only the video-level annotation is available during the training process. To address this problem, we propos…
Conflict-Based Cross-View Consistency for Semi-Supervised Semantic Segmentation
Zicheng Wang, Zhen Zhao, Xiaoxia Xing +3
Semi-supervised semantic segmentation (SSS) has recently gained increasing research interest as it can reduce the requirement for large-scale fully-annotated training data. The cur…
Bridging Synthetic and Real Images: a Transferable and Multiple Consistency aided Fundus Image Enhancement Framework
Erjian Guo, Huazhu Fu, Luping Zhou +1
Deep learning based image enhancement models have largely improved the readability of fundus images in order to decrease the uncertainty of clinical observations and the risk of mi…
VoxelContext-Net: An Octree based Framework for Point Cloud Compression
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. Taking advantages of both octree based me…
FVC: A New Framework towards Deep Video Compression in Feature Space
Zhihao Hu, Guo Lu, Dong Xu
Learning based video compression attracts increasing attention in the past few years. The previous hybrid coding approaches rely on pixel space operations to reduce spatial and tem…
Back-tracing Representative Points for Voting-based 3D Object Detection in Point Clouds
Bowen Cheng, Lu Sheng, Shaoshuai Shi +2
3D object detection in point clouds is a challenging vision task that benefits various applications for understanding the 3D visual world. Lots of recent research focuses on how to…
VDM-DA: Virtual Domain Modeling for Source Data-free Domain Adaptation
Jiayi Tian, Jing Zhang, Wen Li +1
Domain adaptation aims to leverage a label-rich domain (the source domain) to help model learning in a label-scarce domain (the target domain). Most domain adaptation methods requi…
Salient Object Detection via Integrity Learning
Mingchen Zhuge, Deng-Ping Fan, Nian Liu +3
Although current salient object detection (SOD) works have achieved significant progress, they are limited when it comes to the integrity of the predicted salient regions. We defin…
Inception Convolution with Efficient Dilation Search
Jie Liu, Chuming Li, Feng Liang +5
As a variant of standard convolution, a dilated convolution can control effective receptive fields and handle large scale variance of objects without introducing additional computa…
Human-centric Spatio-Temporal Video Grounding With Visual Transformers
Zongheng Tang, Yue Liao, Si Liu +5
In this work, we introduce a novel task - Humancentric Spatio-Temporal Video Grounding (HC-STVG). Unlike the existing referring expression tasks in images or videos, by focusing on…
Improving AMR Parsing with Sequence-to-Sequence Pre-training
Dongqin Xu, Junhui Li, Muhua Zhu +2
In the literature, the research on abstract meaning representation (AMR) parsing is much restricted by the size of human-curated dataset which is critical to build an AMR parser wi…
Improving Deep Video Compression by Resolution-adaptive Flow Coding
Zhihao Hu, Zhenghao Chen, Dong Xu +3
In the learning based video compression approaches, it is an essential issue to compress pixel-level optical flow maps by developing new motion vector (MV) encoders. In this work,…
Content Adaptive and Error Propagation Aware Deep Video Compression
Guo Lu, Chunlei Cai, Xiaoyun Zhang +4
Recently, learning based video compression methods attract increasing attention. However, the previous works suffer from error propagation due to the accumulation of reconstructed…
Channel Pruning Guided by Classification Loss and Feature Importance
Jinyang Guo, Wanli Ouyang, Dong Xu
In this work, we propose a new layer-by-layer channel pruning method called Channel Pruning guided by classification Loss and feature Importance (CPLI). In contrast to the existing…
A Unified End-to-End Framework for Efficient Deep Image Compression
Jiaheng Liu, Guo Lu, Zhihao Hu +1
Image compression is a widely used technique to reduce the spatial redundancy in images. Recently, learning based image compression has achieved significant progress by using the p…
IntersectGAN: Learning Domain Intersection for Generating Images with Multiple Attributes
Zehui Yao, Boyan Zhang, Zhiyong Wang +3
Generative adversarial networks (GANs) have demonstrated great success in generating various visual content. However, images generated by existing GANs are often of attributes (e.g…
Refactoring Neural Networks for Verification
David Shriver, Dong Xu, Sebastian Elbaum +1
Deep neural networks (DNN) are growing in capability and applicability. Their effectiveness has led to their use in safety critical and autonomous systems, yet there is a dearth of…
Gated Group Self-Attention for Answer Selection
Dong Xu, Jianhui Ji, Haikuan Huang +2
Answer selection (answer ranking) is one of the key steps in many kinds of question answering (QA) applications, where deep models have achieved state-of-the-art performance. Among…
Hashing based Answer Selection
Dong Xu, Wu-Jun Li
Answer selection is an important subtask of question answering (QA), where deep models usually achieve better performance. Most deep models adopt question-answer interaction mechan…
Progressive Cross-Stream Cooperation in Spatial and Temporal Domain for Action Localization
Rui Su, Dong Xu, Luping Zhou +1
Spatio-temporal action localization consists of three levels of tasks: spatial localization, action classification, and temporal localization. In this work, we propose a new progre…
MUFold-SS: Protein Secondary Structure Prediction Using Deep Inception-Inside-Inception Networks
Chao Fang, Yi Shang, Dong Xu
Motivation: Protein secondary structure prediction can provide important information for protein 3D structure prediction and protein functions. Deep learning, which has been succes…