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CASIA OpenIR
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Reducing Vision-Answer Biases for Multiple-Choice VQA 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2023, 卷号: 32, 页码: 4621-4634
作者:  Zhang, Xi;  Zhang, Feifei;  Xu, Changsheng
Adobe PDF(2684Kb)  |  收藏  |  浏览/下载：82/1  |  提交时间：2023/11/17
Multiple-choice VQA  vision-answer bias  causal intervention  counterfactual interaction learning  
Learning Hierarchical Video Graph Networks for One-Stop Video Delivery 期刊论文
ACM Transactions on Multimedia Computing, Communications, and Applications, 2022, 卷号: 18, 期号: 1, 页码: 1-23
作者:  Song, Yaguang;  Gao, Junyu;  Yang, Xiaoshan;  Xu, Changsheng
Adobe PDF(7608Kb)  |  收藏  |  浏览/下载：171/51  |  提交时间：2023/04/25
Cross modal  video retrieval  deep learning  graph neural networks  
Holographic Feature Learning of Egocentric-Exocentric Videos for Multi-Domain Action Recognition 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2022, 卷号: 24, 页码: 2273-2286
作者:  Huang, Yi;  Yang, Xiaoshan;  Gao, Junyun;  Xu, Changsheng
Adobe PDF(2409Kb)  |  收藏  |  浏览/下载：366/74  |  提交时间：2022/07/25
Videos  Feature extraction  Visualization  Task analysis  Computational modeling  Target recognition  Prototypes  Egocentric videos  exocentric videos  holographic feature  multi-domain  action recognition  
Joint Expression Synthesis and Representation Learning for Facial Expression Recognition 期刊论文
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2022, 卷号: 32, 期号: 3, 页码: 1681-1695
作者:  Zhang, Xi;  Zhang, Feifei;  Xu, Changsheng
Adobe PDF(4827Kb)  |  收藏  |  浏览/下载：260/1  |  提交时间：2022/06/06
Face recognition  Task analysis  Generative adversarial networks  Image synthesis  Image recognition  Faces  Training  Facial expression recognition  facial image synthesis  generative adversarial network  representation learning  
Transformers in computational visual media: A survey 期刊论文
Computational Visual Media, 2021, 卷号: 8, 期号: 1, 页码: 33-62
作者:  Xu,Yifan;  Wei,Huapeng;  Lin,Minxuan;  Deng,Yingying;  Sheng,Kekai;  Zhang,Mengdan;  Tang,Fan;  Dong,Weiming;  Huang,Feiyue;  Xu,Changsheng
Adobe PDF(5366Kb)  |  收藏  |  浏览/下载：319/44  |  提交时间：2021/12/28
visual transformer  computational visual media (CVM)  high-level vision  low-level vision  image generation  multi-modal learning  
Unsupervised Video Summarization via Relation-Aware Assignment Learning 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2021, 卷号: 23, 页码: 3203-3214
作者:  Gao, Junyu;  Yang, Xiaoshan;  Zhang, Yingying;  Xu, Changsheng
Adobe PDF(3649Kb)  |  收藏  |  浏览/下载：342/67  |  提交时间：2021/11/03
Feature extraction  Training  Optimization  Semantics  Recurrent neural networks  Task analysis  Graph neural network  unsupervised learning  video summarization  
Learning Coarse-to-Fine Graph Neural Networks for Video-Text Retrieval 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2021, 卷号: 23, 页码: 2386-2397
作者:  Wang, Wei;  Gao, Junyu;  Yang, Xiaoshan;  Xu, Changsheng
Adobe PDF(2165Kb)  |  收藏  |  浏览/下载：352/47  |  提交时间：2021/11/02
Feature extraction  Encoding  Task analysis  Semantics  Data models  Cognition  Focusing  Video-text retrieval  graph neural network  coarse-to-fine strategy  
Knowledge-driven Egocentric Multimodal Activity Recognition 期刊论文
ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 2020, 卷号: 16, 期号: 4, 页码: 21
作者:  Huang, Yi;  Yang, Xiaoshan;  Gao, Junyu;  Sang, Jitao;  Xu, Changsheng
Adobe PDF(1875Kb)  |  收藏  |  浏览/下载：423/67  |  提交时间：2021/03/08
Egocentric videos  wearable sensors  graph neural networks  
Self-Supervised Feature Augmentation for Large Image Object Detection 期刊论文
IEEE Transactions on Image Processing, 2020, 卷号: 29, 期号: 0, 页码: 6745-6758
作者:  Pan, Xingjia;  Tang, Fan;  Dong, Weiming;  Gu, Yang;  Song, Zhichao;  Meng, Yiping;  Xu, Pengfei;  Oliver, Deussen;  Xu, Changsheng
浏览  |  Adobe PDF(5411Kb)  |  收藏  |  浏览/下载：324/74  |  提交时间：2020/12/21
object detection  large image  self-supervise  feature augmentation  
Relative coordinates constraint for face alignment 期刊论文
NEUROCOMPUTING, 2020, 卷号: 395, 页码: 119-127
作者:  Nian, Fudong;  Li, Teng;  Bao, Bing-Kun;  Xu, Changsheng
收藏  |  浏览/下载：275/0  |  提交时间：2020/06/22
Face alignment  Relative coordinates constraint  CNN  Loss function design