Zobrazeno 1 - 10
of 669
pro vyhledávání: '"LI, Sicheng"'
With the continuous advancement of processors, modern micro-architecture designs have become increasingly complex. The vast design space presents significant challenges for human designers, making design space exploration (DSE) algorithms a significa
Externí odkaz:
http://arxiv.org/abs/2412.10754
The emergence of Neural Radiance Fields (NeRF) has greatly impacted 3D scene modeling and novel-view synthesis. As a kind of visual media for 3D scene representation, compression with high rate-distortion performance is an eternal target. Motivated b
Externí odkaz:
http://arxiv.org/abs/2404.02185
Autor:
Li, Sicheng, Sun, Keqiang, Lai, Zhixin, Wu, Xiaoshi, Qiu, Feng, Xie, Haoran, Miyata, Kazunori, Li, Hongsheng
The conditional text-to-image diffusion models have garnered significant attention in recent years. However, the precision of these models is often compromised mainly for two reasons, ambiguous condition input and inadequate condition guidance over s
Externí odkaz:
http://arxiv.org/abs/2403.18417
Recovering 3D geometry and textures of individual objects is crucial for many robotics applications, such as manipulation, pose estimation, and autonomous driving. However, decomposing a target object from a complex background is challenging. Most ex
Externí odkaz:
http://arxiv.org/abs/2310.11092
Neural Radiance Fields (NeRF) have demonstrated superior novel view synthesis performance but are slow at rendering. To speed up the volume rendering process, many acceleration methods have been proposed at the cost of large memory consumption. To pu
Externí odkaz:
http://arxiv.org/abs/2212.08476
Publikováno v:
Shipin Kexue, Vol 45, Iss 13, Pp 300-311 (2024)
Coaxial electrospinning is a new technology for the preparation of multi-structure nanofibers, with the advantages of simple equipment operation, mild processing conditions and adjustable structure. This technology uses a direct current (DC) high vol
Externí odkaz:
https://doaj.org/article/2fba0b4931024f968a2440d8ba4bb59a
Publikováno v:
In Geoderma January 2025 453
Publikováno v:
In Journal of Water Process Engineering January 2025 69
Publikováno v:
In Social Science & Medicine January 2025 364
Graph convolutional networks have been widely used for skeleton-based action recognition due to their excellent modeling ability of non-Euclidean data. As the graph convolution is a local operation, it can only utilize the short-range joint dependenc
Externí odkaz:
http://arxiv.org/abs/2206.13028