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pro vyhledávání: '"chen, Bin"'
Utilizing the multi-dimensional (MD) space for constellation shaping has been proven to be an effective approach for achieving shaping gains. Despite there exists a variety of MD modulation formats tailored for specific optical transmission scenarios
Externí odkaz:
http://arxiv.org/abs/2412.16236
Autor:
Wang, Jinpeng, Lian, Niu, Li, Jun, Wang, Yuting, Feng, Yan, Chen, Bin, Zhang, Yongbing, Xia, Shu-Tao
Self-supervised video hashing (SSVH) is a practical task in video indexing and retrieval. Although Transformers are predominant in SSVH for their impressive temporal modeling capabilities, they often suffer from computational and memory inefficiencie
Externí odkaz:
http://arxiv.org/abs/2412.14518
This article introduces the $L_p$-Gauss dual curvature measure and proposes its related $L_p$-Gauss dual Minkowski problem as: for $p,q\in\mathbb{R}$, under what necessary and/or sufficient condition on a non-zero finite Borel measure $\mu$ on unit s
Externí odkaz:
http://arxiv.org/abs/2412.13557
Autor:
Peng, Xin, Liu, Zhihao, Zhang, Shengnan, Zhou, Yi, Sun, Yuran, Su, Yahui, Wu, Chunxiang, Zhou, Tingyu, Liu, Le, Li, Yazhou, Wang, Hangdong, Yang, Jinhu, Chen, Bin, Li, Yuke, Xi, Chuanying, Du, Jianhua, Jiao, Zhiwei, Wu, Quansheng, Fang, Minghu
As a prototypical altermagnet, RuO$_{2}$ has been subject to many controversial reports regarding its magnetic ground state and the existence of crystal Hall effects. We obtained high-quality RuO$_{2}$ single crystal with a residual resistivity ratio
Externí odkaz:
http://arxiv.org/abs/2412.12258
Autor:
Peng, Xin, Wang, Yuzhi, Zhang, Shengnan, Zhou, Yi, Sun, Yuran, Su, Yahui, Wu, Chunxiang, Zhou, Tingyu, Liu, Le, Wang, Hangdong, Yang, Jinhu, Chen, Bin, Fang, Zhong, Du, Jianhua, Jiao, Zhiwei, Wu, Quansheng, Fang, Minghu
The discovery of altermagnet (AM) marks a significant advancement in magnetic materials, combining characteristics of both ferromagnetism and antiferromagnetism. In this Letter, we focus on CrSb, which has been verified to be an AM and to exhibit sub
Externí odkaz:
http://arxiv.org/abs/2412.12263
Dataset distillation offers an efficient way to reduce memory and computational costs by optimizing a smaller dataset with performance comparable to the full-scale original. However, for large datasets and complex deep networks (e.g., ImageNet-1K wit
Externí odkaz:
http://arxiv.org/abs/2412.09959
Dataset distillation (DD) aims to minimize the time and memory consumption needed for training deep neural networks on large datasets, by creating a smaller synthetic dataset that has similar performance to that of the full real dataset. However, cur
Externí odkaz:
http://arxiv.org/abs/2412.09945
RealOSR: Latent Unfolding Boosting Diffusion-based Real-world Omnidirectional Image Super-Resolution
Omnidirectional image super-resolution (ODISR) aims to upscale low-resolution (LR) omnidirectional images (ODIs) to high-resolution (HR), addressing the growing demand for detailed visual content across a $180^{\circ}\times360^{\circ}$ viewport. Exis
Externí odkaz:
http://arxiv.org/abs/2412.09646
3D Gaussian Splatting (3DGS) has emerged as a pivotal technique for 3D scene representation, providing rapid rendering speeds and high fidelity. As 3DGS gains prominence, safeguarding its intellectual property becomes increasingly crucial since 3DGS
Externí odkaz:
http://arxiv.org/abs/2412.05695
Autor:
Zhang, Xuanyu, Tang, Zecheng, Xu, Zhipei, Li, Runyi, Xu, Youmin, Chen, Bin, Gao, Feng, Zhang, Jian
With the rapid growth of generative AI and its widespread application in image editing, new risks have emerged regarding the authenticity and integrity of digital content. Existing versatile watermarking approaches suffer from trade-offs between tamp
Externí odkaz:
http://arxiv.org/abs/2412.01615