Zobrazeno 1 - 10
of 174
pro vyhledávání: '"Li, Fanzhang"'
The rapid development of generative diffusion models has significantly advanced the field of style transfer. However, most current style transfer methods based on diffusion models typically involve a slow iterative optimization process, e.g., model f
Externí odkaz:
http://arxiv.org/abs/2401.15636
The recent end-to-end neural solvers have shown promise for small-scale routing problems but suffered from limited real-time scaling-up performance. This paper proposes GLOP (Global and Local Optimization Policies), a unified hierarchical framework t
Externí odkaz:
http://arxiv.org/abs/2312.08224
Few-shot image classification aims to classify images from unseen novel classes with few samples. Recent works demonstrate that deep local descriptors exhibit enhanced representational capabilities compared to image-level features. However, most exis
Externí odkaz:
http://arxiv.org/abs/2312.05449
Few-shot image classification has received considerable attention for addressing the challenge of poor classification performance with limited samples in novel classes. However, numerous studies have employed sophisticated learning strategies and div
Externí odkaz:
http://arxiv.org/abs/2310.03517
Image cartoonization has attracted significant interest in the field of image generation. However, most of the existing image cartoonization techniques require re-training models using images of cartoon style. In this paper, we present CartoonDiff, a
Externí odkaz:
http://arxiv.org/abs/2309.08251
Publikováno v:
In Expert Systems With Applications 15 March 2024 238 Part F
Publikováno v:
In Expert Systems With Applications 15 March 2024 238 Part E
Publikováno v:
In Expert Systems With Applications 1 March 2024 237 Part B
Publikováno v:
In Pattern Recognition October 2023 142