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pro vyhledávání: '"Guo,Jun"'
Proper guidance strategies are essential to get optimal generation results without re-training diffusion and flow-based text-to-image models. However, existing guidances either require specific training or strong inductive biases of neural network ar
Externí odkaz:
http://arxiv.org/abs/2412.05827
Diffusion and flow models have achieved remarkable successes in various applications such as text-to-image generation. However, these models typically rely on the same predetermined denoising schedules during inference for each prompt, which potentia
Externí odkaz:
http://arxiv.org/abs/2412.01243
Autor:
Wang, Xinran, Zhang, Haiwen, Li, Baoteng, Liang, Kongming, Sun, Hao, He, Zhongjiang, Ma, Zhanyu, Guo, Jun
Object description plays an important role for visually impaired individuals to understand and compare the differences between objects. Recent multimodal large language models (MLLMs) exhibit powerful perceptual abilities and demonstrate impressive p
Externí odkaz:
http://arxiv.org/abs/2411.19106
The Vision Transformer (ViT) has achieved notable success in computer vision, with its variants extensively validated across various downstream tasks, including semantic segmentation. However, designed as general-purpose visual encoders, ViT backbone
Externí odkaz:
http://arxiv.org/abs/2411.17061
Autor:
Chen, Jing, Chen, Ji-Yuan, Chen, Jun-Feng, Chen, Xiang, Fu, Chang-Bo, Guo, Jun, Guo, Yi-Han, Khaw, Kim Siang, Li, Jia-Lin, Li, Liang, Li, Shu, Lin, Yu-ming, Liu, Dan-Ning, Liu, Kang, Liu, Kun, Liu, Qi-Bin, Liu, Zhi, Lu, Ze-Jia, Lv, Meng, Song, Si-Yuan, Sun, Tong, Tang, Jian-Nan, Wan, Wei-Shi, Wang, Dong, Wang, Xiao-Long, Wang, Yu-Feng, Wang, Zhen, Wang, Zi-Rui, Wu, Wei-Hao, Yang, Hai-Jun, Yang, Lin, Yang, Yong, Yu, Dian, Yuan, Rui, Zhang, Jun-Hua, Zhang, Yu-Lei, Zhang, Yun-Long, Zhao, Zhi-Yu, Zhou, Bai-Hong, Zhu, Chun-Xiang, Zhu, Xu-Liang, Zhu, Yi-Fan
DarkSHINE is a newly proposed fixed-target experiment initiative to search for the invisible decay of Dark Photon via missing energy/momentum signatures, based on the high repetition rate electron beam to be deployed/delivered by the Shanghai High re
Externí odkaz:
http://arxiv.org/abs/2411.09345
In the realm of Artificial Intelligence Generated Content (AIGC), flow-matching models have emerged as a powerhouse, achieving success due to their robust theoretical underpinnings and solid ability for large-scale generative modeling. These models h
Externí odkaz:
http://arxiv.org/abs/2410.19310
Publikováno v:
NeurIPS 2024
Despite their strong performances on many generative tasks, diffusion models require a large number of sampling steps in order to generate realistic samples. This has motivated the community to develop effective methods to distill pre-trained diffusi
Externí odkaz:
http://arxiv.org/abs/2410.16794
Primordial black holes (PBHs), originating from the gravitational collapse of large overdensities in the early Universe, emerge as a compelling dark matter (DM) candidate across a broad mass range. Of particular interest are ultra-light PBHs with mas
Externí odkaz:
http://arxiv.org/abs/2409.14731
The CNN has achieved excellent results in the automatic classification of medical images. In this study, we propose a novel deep residual 3D attention non-local network (NL-RAN) to classify CT images included COVID-19, common pneumonia, and normal to
Externí odkaz:
http://arxiv.org/abs/2408.04300