Search Results for author: Chang Wen Chen

Found 28 papers, 7 papers with code

End-to-End Personalized Next Location Recommendation via Contrastive User Preference Modeling

no code implementations22 Mar 2023 Yan Luo, Ye Liu, Fu-Lai Chung, Yu Liu, Chang Wen Chen

History encoder is designed to model mobility patterns from historical check-in sequences, while query generator explicitly learns user preferences to generate user-specific intention queries.

Interventional Bag Multi-Instance Learning On Whole-Slide Pathological Images

1 code implementation13 Mar 2023 Tiancheng Lin, Zhimiao Yu, Hongyu Hu, Yi Xu, Chang Wen Chen

This deficiency is a confounder that limits the performance of existing MIL methods.

Statistical QoS Provisioning Analysis and Performance Optimization in xURLLC-enabled Massive MU-MIMO Networks: A Stochastic Network Calculus Perspective

no code implementations20 Feb 2023 Yuang Chen, Hancheng Lu, Langtian Qin, Chenwu Zhang, Chang Wen Chen

In this paper, fundamentals and performance tradeoffs of the neXt-generation ultra-reliable and low-latency communication (xURLLC) are investigated from the perspective of stochastic network calculus (SNC).

Novel Concepts

Being Comes from Not-being: Open-vocabulary Text-to-Motion Generation with Wordless Training

no code implementations28 Oct 2022 Junfan Lin, Jianlong Chang, Lingbo Liu, Guanbin Li, Liang Lin, Qi Tian, Chang Wen Chen

During inference, instead of changing the motion generator, our method reformulates the input text into a masked motion as the prompt for the motion generator to ``reconstruct'' the motion.

Language Modelling Zero-Shot Learning

Towards a Unified View on Visual Parameter-Efficient Transfer Learning

1 code implementation3 Oct 2022 Bruce X. B. Yu, Jianlong Chang, Lingbo Liu, Qi Tian, Chang Wen Chen

Towards this goal, we propose a framework with a unified view of PETL called visual-PETL (V-PETL) to investigate the effects of different PETL techniques, data scales of downstream domains, positions of trainable parameters, and other aspects affecting the trade-off.

Action Recognition Image Classification +2

Learned Video Compression via Heterogeneous Deformable Compensation Network

no code implementations11 Jul 2022 Huairui Wang, Zhenzhong Chen, Chang Wen Chen

In this paper, we propose a learned video compression framework via heterogeneous deformable compensation strategy (HDCVC) to tackle the problems of unstable compression performance caused by single-size deformable kernels in downsampled feature domain.

Motion Compensation Optical Flow Estimation +1

UMT: Unified Multi-modal Transformers for Joint Video Moment Retrieval and Highlight Detection

1 code implementation CVPR 2022 Ye Liu, Siyuan Li, Yang Wu, Chang Wen Chen, Ying Shan, XiaoHu Qie

Finding relevant moments and highlights in videos according to natural language queries is a natural and highly valuable common need in the current video content explosion era.

Highlight Detection Moment Retrieval +2

Taking an Emotional Look at Video Paragraph Captioning

no code implementations12 Mar 2022 Qinyu Li, Tengpeng Li, Hanli Wang, Chang Wen Chen

In this work, a comprehensive study is conducted on video paragraph captioning, with the goal to generate paragraph-level descriptions for a given video.

Image Captioning

Knowledge-enriched Attention Network with Group-wise Semantic for Visual Storytelling

no code implementations10 Mar 2022 Tengpeng Li, Hanli Wang, Bin He, Chang Wen Chen

Third, a unified one-stage story generation model with encoder-decoder structure is proposed to simultaneously train and infer the knowledge-enriched attention network, group-wise semantic module and multi-modal story generation decoder in an end-to-end fashion.

Story Generation Visual Storytelling

Learning to Aggregate Multi-Scale Context for Instance Segmentation in Remote Sensing Images

1 code implementation22 Nov 2021 Ye Liu, Huifang Li, Chao Hu, Shuang Luo, Yan Luo, Chang Wen Chen

The proposed model exploits three lightweight plug-and-play modules, namely dense feature pyramid network (DenseFPN), spatial context pyramid (SCP), and hierarchical region of interest extractor (HRoIE), to aggregate global visual context at feature, spatial, and instance domains, respectively.

Instance Segmentation Object Detection

Optimized Separable Convolution: Yet Another Efficient Convolution Operator

no code implementations29 Sep 2021 Tao Wei, Yonghong Tian, YaoWei Wang, Yun Liang, Chang Wen Chen

In this research, we propose a novel and principled operator called optimized separable convolution by optimal design for the internal number of groups and kernel sizes for general separable convolutions can achieve the complexity of O(C^{\frac{3}{2}}K).

Rethinking Convolution: Towards an Optimal Efficiency

no code implementations1 Jan 2021 Tao Wei, Yonghong Tian, Chang Wen Chen

In this research, we propose a novel operator called \emph{optimal separable convolution} which can be calculated at $O(C^{\frac{3}{2}}KHW)$ by optimal design for the internal number of groups and kernel sizes for general separable convolutions.

ConsNet: Learning Consistency Graph for Zero-Shot Human-Object Interaction Detection

2 code implementations14 Aug 2020 Ye Liu, Junsong Yuan, Chang Wen Chen

We consider the problem of Human-Object Interaction (HOI) Detection, which aims to locate and recognize HOI instances in the form of <human, action, object> in images.

Human-Object Interaction Detection Zero-Shot Human-Object Interaction Detection

Fusing Motion Patterns and Key Visual Information for Semantic Event Recognition in Basketball Videos

no code implementations13 Jul 2020 Lifang Wu, Zhou Yang, Qi. Wang, Meng Jian, Boxuan Zhao, Junchi Yan, Chang Wen Chen

Based on the observations, we propose a scheme to fuse global and local motion patterns (MPs) and key visual information (KVI) for semantic event recognition in basketball videos.

Group Activity Recognition Optical Flow Estimation

From Caesar Cipher to Unsupervised Learning: A New Method for Classifier Parameter Estimation

no code implementations6 Jun 2019 Yu Liu, Li Deng, Jianshu Chen, Chang Wen Chen

To remove the need for the parallel training corpora has practical significance for real-world applications, and it is one of the main goals of unsupervised learning.

General Classification Language Modelling +3

AVT: Unsupervised Learning of Transformation Equivariant Representations by Autoencoding Variational Transformations

1 code implementation ICCV 2019 Guo-Jun Qi, Liheng Zhang, Chang Wen Chen, Qi Tian

This ensures the resultant TERs of individual images contain the {\em intrinsic} information about their visual structures that would equivary {\em extricably} under various transformations in a generalized {\em nonlinear} case.

Ontology Based Global and Collective Motion Patterns for Event Classification in Basketball Videos

no code implementations16 Mar 2019 Lifang Wu, Zhou Yang, Jiaoyu He, Meng Jian, Yaowen Xu, Dezhong Xu, Chang Wen Chen

Therefore, a semantic event in broadcast basketball videos is closely related to both the global motion (camera motion) and the collective motion.

Classification General Classification +1

DA-GAN: Instance-Level Image Translation by Deep Attention Generative Adversarial Networks

no code implementations CVPR 2018 Shuang Ma, Jianlong Fu, Chang Wen Chen, Tao Mei

Specifically, we jointly learn a deep attention encoder, and the instance-level correspondences could be consequently discovered through attending on the learned instances.

Data Augmentation Deep Attention +2

DA-GAN: Instance-level Image Translation by Deep Attention Generative Adversarial Networks (with Supplementary Materials)

no code implementations CVPR 2018 Shuang Ma, Jianlong Fu, Chang Wen Chen, Tao Mei

Specifically, we jointly learn a deep attention encoder, and the instancelevel correspondences could be consequently discovered through attending on the learned instance pairs.

Data Augmentation Deep Attention +1

Fully Point-wise Convolutional Neural Network for Modeling Statistical Regularities in Natural Images

no code implementations19 Jan 2018 Jing Zhang, Yang Cao, Yang Wang, Chenglin Wen, Chang Wen Chen

Specifically, we propose to randomly shuffle the pixels in the origin images and leverage the shuffled image as input to make CNN more concerned with the statistical properties.

Color Constancy Image Dehazing

Network Iterative Learning for Dynamic Deep Neural Networks via Morphism

no code implementations ICLR 2018 Tao Wei, Changhu Wang, Chang Wen Chen

In this research, we present a novel learning scheme called network iterative learning for deep neural networks.

Fast Haze Removal for Nighttime Image Using Maximum Reflectance Prior

no code implementations CVPR 2017 Jing Zhang, Yang Cao, Shuai Fang, Yu Kang, Chang Wen Chen

Then, we propose a simple but effective image prior, maximum reflectance prior, to estimate the varying ambient illumination.

Modularized Morphing of Neural Networks

no code implementations12 Jan 2017 Tao Wei, Changhu Wang, Chang Wen Chen

Different from existing work where basic morphing types on the layer level were addressed, we target at the central problem of network morphism at a higher level, i. e., how a convolutional layer can be morphed into an arbitrary module of a neural network.

Storytelling of Photo Stream with Bidirectional Multi-thread Recurrent Neural Network

no code implementations2 Jun 2016 Yu Liu, Jianlong Fu, Tao Mei, Chang Wen Chen

Second, by using sGRU as basic units, the BMRNN is trained to align the local storylines into the global sequential timeline.

Video Captioning Visual Storytelling

Network Morphism

no code implementations5 Mar 2016 Tao Wei, Changhu Wang, Yong Rui, Chang Wen Chen

The second requirement for this network morphism is its ability to deal with non-linearity in a network.

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