Zobrazeno 1 - 10
of 18 983
pro vyhledávání: '"CHEN, GUANG"'
Autor:
Chen, Zhiyuan, Lu, Fan, Yu, Guo, Li, Bin, Qu, Sanqing, Huang, Yuan, Fu, Changhong, Chen, Guang
Tracking the 6DoF pose of unknown objects in monocular RGB video sequences is crucial for robotic manipulation. However, existing approaches typically rely on accurate depth information, which is non-trivial to obtain in real-world scenarios. Althoug
Externí odkaz:
http://arxiv.org/abs/2412.02267
Autor:
Chen, Guang-Jie, Zhao, Dong, Wang, Zhu-Bo, Li, Ziqin, Zhang, Ji-Zhe, Chen, Liang, Zhang, Yan-Lei, Xu, Xin-Biao, Liu, Ai-Ping, Dong, Chun-Hua, Guo, Guang-Can, Huang, Kun, Zou, Chang-Ling
Precise control and manipulation of neutral atoms are essential for quantum technologies but largely dependent on conventional bulky optical setups. Here, we demonstrate a multifunctional metalens that integrates an achromatic lens with large numeric
Externí odkaz:
http://arxiv.org/abs/2411.05501
The proliferation of Internet memes in the age of social media necessitates effective identification of harmful ones. Due to the dynamic nature of memes, existing data-driven models may struggle in low-resource scenarios where only a few labeled exam
Externí odkaz:
http://arxiv.org/abs/2411.05383
Autor:
Yu, Huizi, Zhou, Jiayan, Li, Lingyao, Chen, Shan, Gallifant, Jack, Shi, Anye, Li, Xiang, Hua, Wenyue, Jin, Mingyu, Chen, Guang, Zhou, Yang, Li, Zhao, Gupte, Trisha, Chen, Ming-Li, Azizi, Zahra, Zhang, Yongfeng, Assimes, Themistocles L., Ma, Xin, Bitterman, Danielle S., Lu, Lin, Fan, Lizhou
Simulated patient systems play a crucial role in modern medical education and research, providing safe, integrative learning environments and enabling clinical decision-making simulations. Large Language Models (LLM) could advance simulated patient s
Externí odkaz:
http://arxiv.org/abs/2409.18924
Generative language models (LMs) offer numerous advantages but may produce inappropriate or harmful outputs due to the harmful knowledge acquired during pre-training. This knowledge often manifests as undesirable correspondences, such as "harmful pro
Externí odkaz:
http://arxiv.org/abs/2408.09459
Autor:
Zhang, Ruiqi, Hou, Jing, Walter, Florian, Gu, Shangding, Guan, Jiayi, Röhrbein, Florian, Du, Yali, Cai, Panpan, Chen, Guang, Knoll, Alois
Reinforcement Learning (RL) is a potent tool for sequential decision-making and has achieved performance surpassing human capabilities across many challenging real-world tasks. As the extension of RL in the multi-agent system domain, multi-agent RL (
Externí odkaz:
http://arxiv.org/abs/2408.09675
In frame-based vision, object detection faces substantial performance degradation under challenging conditions due to the limited sensing capability of conventional cameras. Event cameras output sparse and asynchronous events, providing a potential s
Externí odkaz:
http://arxiv.org/abs/2407.12582
Autor:
Zou, Tianpei, Qu, Sanqing, Li, Zhijun, Knoll, Alois, He, Lianghua, Chen, Guang, Jiang, Changjun
Publikováno v:
ECCV 2024
3D point cloud segmentation has received significant interest for its growing applications. However, the generalization ability of models suffers in dynamic scenarios due to the distribution shift between test and training data. To promote robustness
Externí odkaz:
http://arxiv.org/abs/2407.12387
Although recent efforts have extended Neural Radiance Fields (NeRF) into LiDAR point cloud synthesis, the majority of existing works exhibit a strong dependence on precomputed poses. However, point cloud registration methods struggle to achieve preci
Externí odkaz:
http://arxiv.org/abs/2407.05597
Large vision-language models (LVLMs) have significantly improved multimodal reasoning tasks, such as visual question answering and image captioning. These models embed multimodal facts within their parameters, rather than relying on external knowledg
Externí odkaz:
http://arxiv.org/abs/2406.11288