Zobrazeno 1 - 10
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pro vyhledávání: '"LI, Yue"'
The field of novel view synthesis from images has seen rapid advancements with the introduction of Neural Radiance Fields (NeRF) and more recently with 3D Gaussian Splatting. Gaussian Splatting became widely adopted due to its efficiency and ability
Externí odkaz:
http://arxiv.org/abs/2411.02229
Enhancing the modular structure of existing systems has attracted substantial research interest, focusing on two main methods: (1) software modularization and (2) identifying design issues (e.g., smells) as refactoring opportunities. However, re-modu
Externí odkaz:
http://arxiv.org/abs/2411.01012
The rapid proliferation of deep neural networks (DNNs) is driving a surge in model watermarking technologies, as the trained deep models themselves serve as intellectual properties. The core of existing model watermarking techniques involves modifyin
Externí odkaz:
http://arxiv.org/abs/2410.20202
In-context learning (ICL) performance is known to be sensitive to the prompt design, yet the impact of class label options in zero-shot classification has been largely overlooked. This study presents the first comprehensive empirical study investigat
Externí odkaz:
http://arxiv.org/abs/2410.19195
The rapid expansion of software systems and the growing number of reported vulnerabilities have emphasized the importance of accurately identifying vulnerable code segments. Traditional methods for vulnerability localization, such as manual code audi
Externí odkaz:
http://arxiv.org/abs/2410.15288
Autor:
Chen, Bolin, Ye, Yan, Chen, Jie, Liao, Ru-Ling, Yin, Shanzhi, Wang, Shiqi, Yang, Kaifa, Li, Yue, Xu, Yiling, Wang, Ye-Kui, Gehlot, Shiv, Su, Guan-Ming, Yin, Peng, McCarthy, Sean, Sullivan, Gary J.
This paper proposes a Generative Face Video Compression (GFVC) approach using Supplemental Enhancement Information (SEI), where a series of compact spatial and temporal representations of a face video signal (i.e., 2D/3D key-points, facial semantics
Externí odkaz:
http://arxiv.org/abs/2410.15105
Automatic subphenotyping from electronic health records (EHRs)provides numerous opportunities to understand diseases with unique subgroups and enhance personalized medicine for patients. However, existing machine learning algorithms either focus on s
Externí odkaz:
http://arxiv.org/abs/2410.13217
For decades, video compression technology has been a prominent research area. Traditional hybrid video compression framework and end-to-end frameworks continue to explore various intra- and inter-frame reference and prediction strategies based on dis
Externí odkaz:
http://arxiv.org/abs/2410.01654
In many domains, such as healthcare, time-series data is often irregularly sampled with varying intervals between observations. This poses challenges for classical time-series models that require equally spaced data. To address this, we propose a nov
Externí odkaz:
http://arxiv.org/abs/2410.02133