Zobrazeno 1 - 10
of 40 053
pro vyhledávání: '"Li,Ling"'
Autor:
Zhang, Yang, Zhang, Rui, Nie, Xuecheng, Li, Haochen, Chen, Jikun, Hao, Yifan, Zhang, Xin, Liu, Luoqi, Li, Ling
Recent text-to-image models have achieved remarkable success in generating high-quality images. However, when tasked with multi-concept generation which creates images containing multiple characters or objects, existing methods often suffer from attr
Externí odkaz:
http://arxiv.org/abs/2409.01327
Autor:
Wanger, Thomas Cherico, Raveloaritiana, Estelle, Zeng, Siyan, Gao, Haixiu, He, Xueqing, Shao, Yiwen, Wu, Panlong, Wyckhuys, Kris A. G., Zhou, Wenwu, Zou, Yi, Zhu, Zengrong, Li, Ling, Cen, Haiyan, Liu, Yunhui, Fan, Shenggen
China is the leading crop producer and has successfully implemented sustainable development programs related to agriculture. Sustainable agriculture has been promoted to achieve national food security targets such as food self-sufficiency through the
Externí odkaz:
http://arxiv.org/abs/2407.01364
Autor:
Shuai, Chenhao, Cai, Rizhao, Dissanayake, Bandara, Newman, Amanda, Guan, Dayan, Sng, Dennis, Li, Ling, Kot, Alex
Face retouching aims to remove facial blemishes, such as pigmentation and acne, and still retain fine-grain texture details. Nevertheless, existing methods just remove the blemishes but focus little on realism of the intermediate process, limiting th
Externí odkaz:
http://arxiv.org/abs/2406.13227
Autor:
Gao, Haihan, Zhang, Rui, Yi, Qi, Yao, Hantao, Li, Haochen, Guo, Jiaming, Peng, Shaohui, Gao, Yunkai, Wang, QiCheng, Hu, Xing, Wen, Yuanbo, Zhang, Zihao, Du, Zidong, Li, Ling, Guo, Qi, Chen, Yunji
Overfitting in RL has become one of the main obstacles to applications in reinforcement learning(RL). Existing methods do not provide explicit semantic constrain for the feature extractor, hindering the agent from learning a unified cross-domain repr
Externí odkaz:
http://arxiv.org/abs/2406.03250
This work tackles the problem of geo-localization with a new paradigm using a large vision-language model (LVLM) augmented with human inference knowledge. A primary challenge here is the scarcity of data for training the LVLM - existing street-view d
Externí odkaz:
http://arxiv.org/abs/2406.18572
Autor:
Guo, Yuxuan, Peng, Shaohui, Guo, Jiaming, Huang, Di, Zhang, Xishan, Zhang, Rui, Hao, Yifan, Li, Ling, Tian, Zikang, Gao, Mingju, Li, Yutai, Gan, Yiming, Liang, Shuai, Zhang, Zihao, Du, Zidong, Guo, Qi, Hu, Xing, Chen, Yunji
Building open agents has always been the ultimate goal in AI research, and creative agents are the more enticing. Existing LLM agents excel at long-horizon tasks with well-defined goals (e.g., `mine diamonds' in Minecraft). However, they encounter di
Externí odkaz:
http://arxiv.org/abs/2405.15414
Recently, Hadfield et al. proposed the Quantum Alternating Operator Ansatz (QAOA+) to tackle Constrained Combinatorial Optimization Problems (CCOPs). This paper proposes a Progressive Quantum Algorithm (PQA) to reduce the required qubits in solving t
Externí odkaz:
http://arxiv.org/abs/2405.04303
In this paper, we propose a physics-inspired contrastive learning paradigm for low-light enhancement, called PIE. PIE primarily addresses three issues: (i) To resolve the problem of existing learning-based methods often training a LLE model with stri
Externí odkaz:
http://arxiv.org/abs/2404.04586
Generative adversial network (GAN) is a type of generative model that maps a high-dimensional noise to samples in target distribution. However, the dimension of noise required in GAN is not well understood. Previous approaches view GAN as a mapping f
Externí odkaz:
http://arxiv.org/abs/2403.09196
Autor:
Xu, Tongda, Zhu, Ziran, Li, Jian, He, Dailan, Wang, Yuanyuan, Sun, Ming, Li, Ling, Qin, Hongwei, Wang, Yan, Liu, Jingjing, Zhang, Ya-Qin
Diffusion Inverse Solvers (DIS) are designed to sample from the conditional distribution $p_{\theta}(X_0|y)$, with a predefined diffusion model $p_{\theta}(X_0)$, an operator $f(\cdot)$, and a measurement $y=f(x'_0)$ derived from an unknown image $x'
Externí odkaz:
http://arxiv.org/abs/2403.12063