Zobrazeno 1 - 10
of 4 426
pro vyhledávání: '"Wang, MengMeng"'
Autor:
Lin, Haonan, Wang, Mengmeng, Wang, Jiahao, An, Wenbin, Chen, Yan, Liu, Yong, Tian, Feng, Dai, Guang, Wang, Jingdong, Wang, Qianying
Text-guided diffusion models have significantly advanced image editing, enabling high-quality and diverse modifications driven by text prompts. However, effective editing requires inverting the source image into a latent space, a process often hinder
Externí odkaz:
http://arxiv.org/abs/2410.18756
Autor:
Lin, Haonan, An, Wenbin, Wang, Jiahao, Chen, Yan, Tian, Feng, Wang, Mengmeng, Dai, Guang, Wang, Qianying, Wang, Jingdong
Recent advancements have shown promise in applying traditional Semi-Supervised Learning strategies to the task of Generalized Category Discovery (GCD). Typically, this involves a teacher-student framework in which the teacher imparts knowledge to the
Externí odkaz:
http://arxiv.org/abs/2409.19659
Aspect-Based Sentiment Analysis (ABSA) in tourism plays a significant role in understanding tourists' evaluations of specific aspects of attractions, which is crucial for driving innovation and development in the tourism industry. However, traditiona
Externí odkaz:
http://arxiv.org/abs/2409.14997
Autor:
Wang, Jiahao, Yan, Caixia, Zhang, Weizhan, Lin, Haonan, Wang, Mengmeng, Dai, Guang, Gong, Tieliang, Sun, Hao, Wang, Jingdong
Text-to-image diffusion models significantly enhance the efficiency of artistic creation with high-fidelity image generation. However, in typical application scenarios like comic book production, they can neither place each subject into its expected
Externí odkaz:
http://arxiv.org/abs/2409.04801
Although the progress made by large models in computer vision, optimization challenges, the complexity of transformer models, computational limitations, and the requirements of practical applications call for simpler designs in model architecture for
Externí odkaz:
http://arxiv.org/abs/2408.16886
Recent advances in Large Language Models (LLMs) have shown inspiring achievements in constructing autonomous agents that rely on language descriptions as inputs. However, it remains unclear how well LLMs can function as few-shot or zero-shot embodied
Externí odkaz:
http://arxiv.org/abs/2406.16294
Autor:
Wang, Jiahao, Yan, Caixia, Lin, Haonan, Zhang, Weizhan, Wang, Mengmeng, Gong, Tieliang, Dai, Guang, Sun, Hao
Text-to-image diffusion models benefit artists with high-quality image generation. Yet their stochastic nature hinders artists from creating consistent images of the same subject. Existing methods try to tackle this challenge and generate consistent
Externí odkaz:
http://arxiv.org/abs/2404.10267
DreamSalon: A Staged Diffusion Framework for Preserving Identity-Context in Editable Face Generation
Autor:
Lin, Haonan, Wang, Mengmeng, Chen, Yan, An, Wenbin, Yao, Yuzhe, Dai, Guang, Wang, Qianying, Liu, Yong, Wang, Jingdong
While large-scale pre-trained text-to-image models can synthesize diverse and high-quality human-centered images, novel challenges arise with a nuanced task of "identity fine editing": precisely modifying specific features of a subject while maintain
Externí odkaz:
http://arxiv.org/abs/2403.19235
A new digital twin (DT) framework with optimal sensor placement (OSP) is proposed to accurately calculate the modal responses and identify the damage ratios of the offshore jacket platforms. The proposed damage identification framework consists of tw
Externí odkaz:
http://arxiv.org/abs/2404.07959
Autor:
Hou, Xiaojun, Xing, Jiazheng, Qian, Yijie, Guo, Yaowei, Xin, Shuo, Chen, Junhao, Tang, Kai, Wang, Mengmeng, Jiang, Zhengkai, Liu, Liang, Liu, Yong
Multimodal Visual Object Tracking (VOT) has recently gained significant attention due to its robustness. Early research focused on fully fine-tuning RGB-based trackers, which was inefficient and lacked generalized representation due to the scarcity o
Externí odkaz:
http://arxiv.org/abs/2403.16002