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- research-articleNovember 2024
3D-ISRNet: Generating 3D point clouds through image similarity retrieval in a complex background from a single image
AbstractReconstructing the 3D shape of objects using limited information from a single image is a complex and necessary task. The existing methods for reconstructing point clouds from a single image haven't effectively addressed the issue of background ...
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Highlights- Proposed reconstruct point clouds from single images using spatial and channel attention, and symmetric point cloud encoder.
- research-articleOctober 2024
Mining Factors Influencing Emotion Polarization in the Context of Disastrous Emergency Based on Machine Learning
ICBDC '24: Proceedings of the 2024 9th International Conference on Big Data and ComputingPages 39–44https://doi.org/10.1145/3695220.3695222The world has seen a substantial number of disastrous emergencies, which lead to heated discussion on the Internet and then chaos without proper interference. Motivated by others’ emotions through online discussion, netizens actively interact with each ...
- research-articleApril 2022
3D-ARNet: An accurate 3D point cloud reconstruction network from a single-image
Multimedia Tools and Applications (MTAA), Volume 81, Issue 9Pages 12127–12140https://doi.org/10.1007/s11042-021-11433-7AbstractGenerating a more realistic 3D reconstruction point cloud is an ill-posed problem. It is a challenging task to infer 3D shape from a single image. In this paper, a two-stage training network that can reconstruct point cloud from a single image is ...