Zobrazeno 1 - 10
of 37 961
pro vyhledávání: '"ZHANG, Kai"'
Autor:
Jiang, Hanwen, Xu, Zexiang, Xie, Desai, Chen, Ziwen, Jin, Haian, Luan, Fujun, Shu, Zhixin, Zhang, Kai, Bi, Sai, Sun, Xin, Gu, Jiuxiang, Huang, Qixing, Pavlakos, Georgios, Tan, Hao
We propose scaling up 3D scene reconstruction by training with synthesized data. At the core of our work is MegaSynth, a procedurally generated 3D dataset comprising 700K scenes - over 50 times larger than the prior real dataset DL3DV - dramatically
Externí odkaz:
http://arxiv.org/abs/2412.14166
Autor:
Shen, Xuan, Song, Zhao, Zhou, Yufa, Chen, Bo, Li, Yanyu, Gong, Yifan, Zhang, Kai, Tan, Hao, Kuen, Jason, Ding, Henghui, Shu, Zhihao, Niu, Wei, Zhao, Pu, Wang, Yanzhi, Gu, Jiuxiang
Diffusion Transformers have emerged as the preeminent models for a wide array of generative tasks, demonstrating superior performance and efficacy across various applications. The promising results come at the cost of slow inference, as each denoisin
Externí odkaz:
http://arxiv.org/abs/2412.12444
This study investigates the effects of Thom disks on alleviating ground effects by wall-mounted rotating cylinders, also known as Flettner rotors, which utilize wind energy for ship propulsion. Through three-dimensional direct numerical simulations,
Externí odkaz:
http://arxiv.org/abs/2412.12240
Autor:
Sun, Yuxuan, Si, Yixuan, Zhu, Chenglu, Gong, Xuan, Zhang, Kai, Chen, Pingyi, Zhang, Ye, Shui, Zhongyi, Lin, Tao, Yang, Lin
The emergence of large multimodal models (LMMs) has brought significant advancements to pathology. Previous research has primarily focused on separately training patch-level and whole-slide image (WSI)-level models, limiting the integration of learne
Externí odkaz:
http://arxiv.org/abs/2412.12077
Autor:
Peng, Jingyu, Wang, Maolin, Zhao, Xiangyu, Zhang, Kai, Wang, Wanyu, Jia, Pengyue, Liu, Qidong, Guo, Ruocheng, Liu, Qi
Large language models (LLMs) have made remarkable strides in complex reasoning tasks, but their safety and robustness in reasoning processes remain underexplored. Existing attacks on LLM reasoning are constrained by specific settings or lack of imper
Externí odkaz:
http://arxiv.org/abs/2412.11934
Classifier-free guidance (CFG) is widely used in diffusion models but often introduces over-contrast and over-saturation artifacts at higher guidance strengths. We present EP-CFG (Energy-Preserving Classifier-Free Guidance), which addresses these iss
Externí odkaz:
http://arxiv.org/abs/2412.09966
Recent advances in diffusion and flow-based generative models have demonstrated remarkable success in image restoration tasks, achieving superior perceptual quality compared to traditional deep learning approaches. However, these methods either requi
Externí odkaz:
http://arxiv.org/abs/2412.09465
Protein inverse folding is a fundamental problem in bioinformatics, aiming to recover the amino acid sequences from a given protein backbone structure. Despite the success of existing methods, they struggle to fully capture the intricate inter-residu
Externí odkaz:
http://arxiv.org/abs/2412.09380
A spectrum of new hardware has been studied to accelerate database systems in the past decade. Specifically, CUDA cores are known to benefit from the fast development of GPUs and make notable performance improvements. The state-of-the-art GPU-based i
Externí odkaz:
http://arxiv.org/abs/2412.09337
Generative models, particularly diffusion models, have made significant success in data synthesis across various modalities, including images, videos, and 3D assets. However, current diffusion models are computationally intensive, often requiring num
Externí odkaz:
http://arxiv.org/abs/2412.05899