Zobrazeno 1 - 10
of 2 282
pro vyhledávání: '"Liu,Xingyu"'
Autor:
Liu, Xingyu Bruce, Fang, Shitao, Shi, Weiyan, Wu, Chien-Sheng, Igarashi, Takeo, Chen, Xiang `Anthony'
One of the long-standing aspirations in conversational AI is to allow them to autonomously take initiatives in conversations, i.e., being proactive. This is especially challenging for multi-party conversations. Prior NLP research focused mainly on pr
Externí odkaz:
http://arxiv.org/abs/2501.00383
Group Re-identification (G-ReID) faces greater complexity than individual Re-identification (ReID) due to challenges like mutual occlusion, dynamic member interactions, and evolving group structures. Prior graph-based approaches have aimed to capture
Externí odkaz:
http://arxiv.org/abs/2412.18766
Autor:
Zhang, Ruida, Li, Chengxi, Zhang, Chenyangguang, Liu, Xingyu, Yuan, Haili, Li, Yanyan, Ji, Xiangyang, Lee, Gim Hee
Realistic scene reconstruction in driving scenarios poses significant challenges due to fast-moving objects. Most existing methods rely on labor-intensive manual labeling of object poses to reconstruct dynamic objects in canonical space and move them
Externí odkaz:
http://arxiv.org/abs/2412.05548
Autor:
Liu, Xingyu, Li, Yingyue, Li, Chengxi, Wang, Gu, Zhang, Chenyangguang, Huang, Ziqin, Ji, Xiangyang
In this report, we provide the technical details of the submitted method GFreeDet, which exploits Gaussian splatting and vision Foundation models for the model-free unseen object Detection track in the BOP 2024 Challenge.
Externí odkaz:
http://arxiv.org/abs/2412.01552
Unseen object pose estimation methods often rely on CAD models or multiple reference views, making the onboarding stage costly. To simplify reference acquisition, we aim to estimate the unseen object's pose through a single unposed RGB-D reference im
Externí odkaz:
http://arxiv.org/abs/2411.16106
Automated unit test generation has been widely studied, with Large Language Models (LLMs) recently showing significant potential. Moreover, in the context of unit test generation, these tools prioritize high code coverage, often at the expense of pra
Externí odkaz:
http://arxiv.org/abs/2410.13542
Fluorescence molecular tomography (FMT) is a real-time, noninvasive optical imaging technology that plays a significant role in biomedical research. Nevertheless, the ill-posedness of the inverse problem poses huge challenges in FMT reconstructions.
Externí odkaz:
http://arxiv.org/abs/2410.06757
In causal inference, estimating heterogeneous treatment effects (HTE) is critical for identifying how different subgroups respond to interventions, with broad applications in fields such as precision medicine and personalized advertising. Although HT
Externí odkaz:
http://arxiv.org/abs/2407.01004
Autor:
Zhou, Jiehui, Wang, Xumeng, Wong, Kam-Kwai, Zhang, Wei, Liu, Xingyu, Zhang, Juntian, Zhu, Minfeng, Chen, Wei
In causal inference, estimating Heterogeneous Treatment Effects (HTEs) from observational data is critical for understanding how different subgroups respond to treatments, with broad applications such as precision medicine and targeted advertising. H
Externí odkaz:
http://arxiv.org/abs/2407.01893
Autor:
Liu, Jian, Sun, Wei, Yang, Hui, Zeng, Zhiwen, Liu, Chongpei, Zheng, Jin, Liu, Xingyu, Rahmani, Hossein, Sebe, Nicu, Mian, Ajmal
Object pose estimation is a fundamental computer vision problem with broad applications in augmented reality and robotics. Over the past decade, deep learning models, due to their superior accuracy and robustness, have increasingly supplanted convent
Externí odkaz:
http://arxiv.org/abs/2405.07801