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pro vyhledávání: '"Hong, Han"'
It is a common problem in robotics to specify the position of each joint of the robot so that the endpoint reaches a certain target in space. This can be solved in two ways, forward kinematics method and inverse kinematics method. However, inverse ki
Externí odkaz:
http://arxiv.org/abs/2410.15341
This paper analyzes the impact of causal manner in the text encoder of text-to-image (T2I) diffusion models, which can lead to information bias and loss. Previous works have focused on addressing the issues through the denoising process. However, the
Externí odkaz:
http://arxiv.org/abs/2410.00321
Text-to-scene generation, transforming textual descriptions into detailed scenes, typically relies on generating key scenarios along predetermined paths, constraining environmental diversity and limiting customization flexibility. To address these li
Externí odkaz:
http://arxiv.org/abs/2409.09575
Autor:
Hong, Han, Zhang, Ruijia
In this paper, we consider the asymptotic $\sigma_k$ Plateau problem in hyperbolic space. We establish $C^2$ estimates for semi-convex complete hypersurfaces satisfying constant $\sigma_k$ curvature with a prescribed asymptotic boundary at the infini
Externí odkaz:
http://arxiv.org/abs/2408.09428
Autor:
Jiang-Lin, Jian-Yu, Huang, Kang-Yang, Lo, Ling, Huang, Yi-Ning, Lin, Terence, Wu, Jhih-Ciang, Shuai, Hong-Han, Cheng, Wen-Huang
Diffusion models revolutionize image generation by leveraging natural language to guide the creation of multimedia content. Despite significant advancements in such generative models, challenges persist in depicting detailed human-object interactions
Externí odkaz:
http://arxiv.org/abs/2407.17911
Autor:
Yao, Yi, Hsu, Chan-Feng, Lin, Jhe-Hao, Xie, Hongxia, Lin, Terence, Huang, Yi-Ning, Shuai, Hong-Han, Cheng, Wen-Huang
In spite of recent advancements in text-to-image generation, limitations persist in handling complex and imaginative prompts due to the restricted diversity and complexity of training data. This work explores how diffusion models can generate images
Externí odkaz:
http://arxiv.org/abs/2407.12579
In this paper, we extend several results established for stable minimal hypersurfaces to $\delta$-stable minimal hypersurfaces. These include the regularity and compactness theorems for immersed $\delta$-stable minimal hypersurfaces in $\mathbb{R}^{n
Externí odkaz:
http://arxiv.org/abs/2407.03222
Autor:
Liu, Hou-I, Tseng, Yu-Wen, Chang, Kai-Cheng, Wang, Pin-Jyun, Shuai, Hong-Han, Cheng, Wen-Huang
Despite notable advancements in the field of computer vision, the precise detection of tiny objects continues to pose a significant challenge, largely owing to the minuscule pixel representation allocated to these objects in imagery data. This challe
Externí odkaz:
http://arxiv.org/abs/2406.05755
This paper provides an overview of the Fake-EmoReact 2021 Challenge, held at the 9th SocialNLP Workshop, in conjunction with NAACL 2021. The challenge requires predicting the authenticity of tweets using reply context and augmented GIF categories fro
Externí odkaz:
http://arxiv.org/abs/2406.04368
Publikováno v:
Proceedings of the 24th International Society for Music Information Retrieval Conference, 174-181. Milan, Italy, November 5-9, 2023
Nowadays, humans are constantly exposed to music, whether through voluntary streaming services or incidental encounters during commercial breaks. Despite the abundance of music, certain pieces remain more memorable and often gain greater popularity.
Externí odkaz:
http://arxiv.org/abs/2405.12847