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pro vyhledávání: '"Chen, Min"'
Axions have aroused widespread research interest because they can solve the strong CP problem and serve as a possible candidate for dark matter. Currently, people have explored a lot of axion detection experiments, including passively detecting the e
Externí odkaz:
http://arxiv.org/abs/2406.16796
Depression recognition based on physiological signals such as functional near-infrared spectroscopy (fNIRS) and electroencephalogram (EEG) has made considerable progress. However, most existing studies ignore the complementarity and semantic consiste
Externí odkaz:
http://arxiv.org/abs/2406.16968
Reconstructing textured meshes from colored point clouds is an important but challenging task in 3D graphics and vision. Most existing methods predict colors as implicit functions in 3D or UV space, suffering from blurry textures or the lack of gener
Externí odkaz:
http://arxiv.org/abs/2406.15811
Autor:
Lin, Ci-Siang, Liu, I-Jieh, Chen, Min-Hung, Wang, Chien-Yi, Liu, Sifei, Wang, Yu-Chiang Frank
Referring Video Object Segmentation (RVOS) aims to segment the object referred to by the query sentence throughout the entire video. Most existing methods require end-to-end training with dense mask annotations, which could be computation-consuming a
Externí odkaz:
http://arxiv.org/abs/2406.12834
The Transformer architecture has recently gained considerable attention in the field of graph representation learning, as it naturally overcomes several limitations of Graph Neural Networks (GNNs) with customized attention mechanisms or positional an
Externí odkaz:
http://arxiv.org/abs/2405.21061
Autor:
Lai, Chun-Mao, Wang, Hsiang-Chun, Hsieh, Ping-Chun, Wang, Yu-Chiang Frank, Chen, Min-Hung, Sun, Shao-Hua
Imitation learning aims to learn a policy from observing expert demonstrations without access to reward signals from environments. Generative adversarial imitation learning (GAIL) formulates imitation learning as adversarial learning, employing a gen
Externí odkaz:
http://arxiv.org/abs/2405.16194
In this study, we address the limitations inherent in most existing vehicle trajectory prediction methodologies that indiscriminately incorporate all agents within a predetermined proximity when accounting for inter-agent interactions. These approach
Externí odkaz:
http://arxiv.org/abs/2405.13152
Finite-temperature orbital-free density functional theory (FT-OFDFT) holds significant promise for simulating warm dense matter due to its favorable scaling with both system size and temperature. However, the lack of the numerically accurate and tran
Externí odkaz:
http://arxiv.org/abs/2405.12527
Federated learning (FL) has attracted widespread attention because it supports the joint training of models by multiple participants without moving private dataset. However, there are still many security issues in FL that deserve discussion. In this
Externí odkaz:
http://arxiv.org/abs/2405.04029
Large 2D vision-language models (2D-LLMs) have gained significant attention by bridging Large Language Models (LLMs) with images using a simple projector. Inspired by their success, large 3D point cloud-language models (3D-LLMs) also integrate point
Externí odkaz:
http://arxiv.org/abs/2405.01413