UM

Browse/Search Results:  1-4 of 4 Help

Selected(0)Clear Items/Page:    Sort:
Transformer-Based Image Inpainting Detection via Label Decoupling and Constrained Adversarial Training Journal article
Yuanman Li, Liangpei Hu, Li Dong, Haiwei Wu, Jinyu Tian, Jiantao Zhou, Xia Li. Transformer-Based Image Inpainting Detection via Label Decoupling and Constrained Adversarial Training[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2024, 34(3), 1857-1872.
Authors:  Yuanman Li;  Liangpei Hu;  Li Dong;  Haiwei Wu;  Jinyu Tian; et al.
Favorite | TC[WOS]:3 TC[Scopus]:3  IF:8.3/7.1 | Submit date:2023/08/28
Inpainting Forensics  Constrained Adversarial Training  Generalizability  Deep Neural Networks  
An Edge-Aware Transformer Framework for Image Inpainting Detection Conference paper
Hu, Liangpei, Li, Yuanman, You, Jiaxiang, Liang, Rongqin, Li, Xia. An Edge-Aware Transformer Framework for Image Inpainting Detection[C], 2022, 648-660.
Authors:  Hu, Liangpei;  Li, Yuanman;  You, Jiaxiang;  Liang, Rongqin;  Li, Xia
Favorite | TC[WOS]:1 TC[Scopus]:1 | Submit date:2022/08/05
Cross Attention  Inpainting Forensics  Transformer  
GIID-NET: GENERALIZABLE IMAGE INPAINTING DETECTION NETWORK Conference paper
Haiwei Wu, Jiantao Zhou. GIID-NET: GENERALIZABLE IMAGE INPAINTING DETECTION NETWORK[C]:IEEE, 2021, 3867-3871.
Authors:  Haiwei Wu;  Jiantao Zhou
Favorite | TC[WOS]:2 TC[Scopus]:3 | Submit date:2022/05/13
Inpainting Forensics  Deep Neural Networks  Generalizability  
IID-Net: Image Inpainting Detection Network via Neural Architecture Search and Attention Journal article
Wu, Haiwei, Zhou, Jiantao. IID-Net: Image Inpainting Detection Network via Neural Architecture Search and Attention[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2021, 32(3), 1172-1185.
Authors:  Wu, Haiwei;  Zhou, Jiantao
Adobe PDF | Favorite | TC[WOS]:54 TC[Scopus]:67  IF:8.3/7.1 | Submit date:2022/03/28
Feature Extraction  Forensics  Forgery  Training  Task Analysis  Semantics  Computer Architecture  Inpainting Forensics  Generalizability  Deep Neural Networks