Zobrazeno 1 - 10
of 434
pro vyhledávání: '"Fan Yuchen"'
Autor:
Fan Yuchen, Liu Keyu
Publikováno v:
Frontiers in Earth Science, Vol 10 (2023)
Focused ion beam scanning electron microscopy (FIB-SEM) is a commonly used three-dimensional (3D) pore-network reconstruction method for shales due to its unique capability in imaging nano-scale pores. However, it has been found that for pore space o
Externí odkaz:
https://doaj.org/article/4c24c985277a457d80ce30b7f96bae12
Autor:
Fan, Yuchen, Zhong, Xin, Zhou, Heng, Zhang, Yuchen, Liang, Mingyu, Xie, Chengxing, Hua, Ermo, Ding, Ning, Zhou, Bowen
Long-Form Question Answering (LFQA) refers to generating in-depth, paragraph-level responses to open-ended questions. Although lots of LFQA methods are developed, evaluating LFQA effectively and efficiently remains challenging due to its high complex
Externí odkaz:
http://arxiv.org/abs/2410.01945
Autor:
Kotovenko, Dmytro, Grebenkova, Olga, Sarafianos, Nikolaos, Paliwal, Avinash, Ma, Pingchuan, Poursaeed, Omid, Mohan, Sreyas, Fan, Yuchen, Li, Yilei, Ranjan, Rakesh, Ommer, Björn
While style transfer techniques have been well-developed for 2D image stylization, the extension of these methods to 3D scenes remains relatively unexplored. Existing approaches demonstrate proficiency in transferring colors and textures but often st
Externí odkaz:
http://arxiv.org/abs/2409.17917
Autor:
Ding, Henghui, Hong, Lingyi, Liu, Chang, Xu, Ning, Yang, Linjie, Fan, Yuchen, Miao, Deshui, Gu, Yameng, Li, Xin, He, Zhenyu, Wang, Yaowei, Yang, Ming-Hsuan, Chai, Jinming, Ma, Qin, Zhang, Junpei, Jiao, Licheng, Liu, Fang, Liu, Xinyu, Zhang, Jing, Zhang, Kexin, Liu, Xu, Li, LingLing, Fang, Hao, Pan, Feiyu, Lu, Xiankai, Zhang, Wei, Cong, Runmin, Tran, Tuyen, Cao, Bin, Zhang, Yisi, Wang, Hanyi, He, Xingjian, Liu, Jing
Despite the promising performance of current video segmentation models on existing benchmarks, these models still struggle with complex scenes. In this paper, we introduce the 6th Large-scale Video Object Segmentation (LSVOS) challenge in conjunction
Externí odkaz:
http://arxiv.org/abs/2409.05847
Autor:
Fan, Yuchen, Zhong, Xin, Wan, Yazhe, Wang, Chengsi, Cheng, Haonan, Wu, Gaoche, Ding, Ning, Zhou, Bowen
Since LLMs emerged, more attention has been paid to abstractive long-form summarization, where longer input sequences indicate more information contained. Nevertheless, the automatic evaluation of such summaries remains underexplored. The current eva
Externí odkaz:
http://arxiv.org/abs/2407.04969
Providing knowledge documents for large language models (LLMs) has emerged as a promising solution to update the static knowledge inherent in their parameters. However, knowledge in the document may conflict with the memory of LLMs due to outdated or
Externí odkaz:
http://arxiv.org/abs/2404.03577
Modern Large Language Models (LLMs) have showcased remarkable prowess in various tasks necessitating sophisticated cognitive behaviors. Nevertheless, a paradoxical performance discrepancy is observed, where these models underperform in seemingly elem
Externí odkaz:
http://arxiv.org/abs/2404.03532
Autor:
Tang, Shitao, Chen, Jiacheng, Wang, Dilin, Tang, Chengzhou, Zhang, Fuyang, Fan, Yuchen, Chandra, Vikas, Furukawa, Yasutaka, Ranjan, Rakesh
This paper presents a neural architecture MVDiffusion++ for 3D object reconstruction that synthesizes dense and high-resolution views of an object given one or a few images without camera poses. MVDiffusion++ achieves superior flexibility and scalabi
Externí odkaz:
http://arxiv.org/abs/2402.12712
Autor:
Fan, Yuchen
We derive the asymptotic behavior of hitting probability at small target of size $O(\epsilon)$ for reflected Brownian motion in domains with suitable smooth boundary conditions, where the boundary of domain contains both reflecting part, absorbing pa
Externí odkaz:
http://arxiv.org/abs/2402.00997
Autor:
Klinghoffer, Tzofi, Xiang, Xiaoyu, Somasundaram, Siddharth, Fan, Yuchen, Richardt, Christian, Raskar, Ramesh, Ranjan, Rakesh
3D reconstruction from a single-view is challenging because of the ambiguity from monocular cues and lack of information about occluded regions. Neural radiance fields (NeRF), while popular for view synthesis and 3D reconstruction, are typically reli
Externí odkaz:
http://arxiv.org/abs/2312.14239