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Hierarchical Attention Network for Open-Set Fine-Grained Recognition 期刊论文
IEEE Transactions on Circuits and Systems for Video Technology, 2023, 页码: 1-14
作者:  Jiayin, Sun;  Hong, Wang;  Qiulei, Dong
Adobe PDF(2596Kb)  |  收藏  |  浏览/下载：25/5  |  提交时间：2024/05/28
Learning to Reduce Scale Differences for Large-Scale Invariant Image Matching 期刊论文
IEEE Transactions on Circuits and Systems for Video Technology, 2023, 卷号: 33, 期号: 3, 页码: 1335 - 1348
作者:  Fu Yujie;  Zhang Pengju;  Liu Bingxi;  Rong Zheng;  Wu Yihong
Adobe PDF(4879Kb)  |  收藏  |  浏览/下载：27/10  |  提交时间：2024/05/28
Image Matching  Large Scale Changes  Scale Difference Reduction  Scale Ratio Estimation  Covisibility-attention-reinforced Matching Module  
Pixel-Wise Grasp Detection via Twin Deconvolution and Multi-Dimensional Attention 期刊论文
IEEE Transactions on Circuits and Systems for Video Technology, 2023, 卷号: 33, 期号: 8, 页码: 4002-4010
作者:  Ren, Guangli;  Geng, Wenjie;  Guan, Peiyu;  Cao, Zhiqiang;  Yu, Junzhi
Adobe PDF(4013Kb)  |  收藏  |  浏览/下载：13/3  |  提交时间：2024/05/28
Towards Spatially Disentangled Manipulation of Face Images With Pre-Trained StyleGANs 期刊论文
IEEE Transactions on Circuits and Systems for Video Technology, 2023, 卷号: 33, 期号: 4, 页码: 1725-1739
作者:  Yunfan Liu;  Qi Li;  Qiyao Deng;  Zhenan Sun
Adobe PDF(10050Kb)  |  收藏  |  浏览/下载：111/35  |  提交时间：2023/06/20
TranSkeleton: Hierarchical Spatial-Temporal Transformer for Skeleton-Based Action Recognition 期刊论文
IEEE Transactions on Circuits and Systems for Video Technology, 2023, 页码: 1-12
作者:  Haowei Liu;  Yongcheng Liu;  Yuxin Chen;  Chunfeng Yuan;  Bing Li;  Weiming Hu
Adobe PDF(1276Kb)  |  收藏  |  浏览/下载：235/82  |  提交时间：2023/04/28
IRAv3: Hierarchical Incremental Rotation Averaging on the Fly 期刊论文
IEEE Transactions on Circuits and Systems for Video Technology, 2023, 卷号: 33, 期号: 4, 页码: 2001-2006
作者:  Gao, Xiang;  Cui, Hainan;  Li, Menghan;  Xie, Zexiao;  Shen, Shuhan
Adobe PDF(1271Kb)  |  收藏  |  浏览/下载：166/32  |  提交时间：2023/04/25
Global structure from motion  Large-scale rotation averaging  On-the-fly epipolar-geometry graph clustering