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Found 10 papers, 2 papers with code
DenseSplat: Densifying Gaussian Splatting SLAM with Neural Radiance Prior
Gaussian SLAM systems excel in real-time rendering and fine-grained reconstruction compared to NeRF-based systems.
GARAD-SLAM: 3D GAussian splatting for Real-time Anti Dynamic SLAM
The 3D Gaussian Splatting (3DGS)-based SLAM system has garnered widespread attention due to its excellent performance in real-time high-fidelity rendering.
DeRainGS: Gaussian Splatting for Enhanced Scene Reconstruction in Rainy Environments
In response to these challenges, this study introduces the novel task of 3D Reconstruction in Rainy Environments (3DRRE), specifically designed to address the complexities of reconstructing 3D scenes under rainy conditions.
Technique Report of CVPR 2024 PBDL Challenges
The intersection of physics-based vision and deep learning presents an exciting frontier for advancing computer vision technologies.
Structure Gaussian SLAM with Manhattan World Hypothesis
Gaussian SLAM systems have made significant advancements in improving the efficiency and fidelity of real-time reconstructions.
Multi-Modal UAV Detection, Classification and Tracking Algorithm -- Technical Report for CVPR 2024 UG2 Challenge
Leveraging this information, we propose a multi-modal UAV detection, classification, and 3D tracking method for accurate UAV classification and tracking.
MoD-SLAM: Monocular Dense Mapping for Unbounded 3D Scene Reconstruction
Monocular SLAM has received a lot of attention due to its simple RGB inputs and the lifting of complex sensor constraints.
SGS-SLAM: Semantic Gaussian Splatting For Neural Dense SLAM
We present SGS-SLAM, the first semantic visual SLAM system based on Gaussian Splatting.
DDN-SLAM: Real-time Dense Dynamic Neural Implicit SLAM
To address dynamic tracking interferences, we propose a feature point segmentation method that combines semantic features with a mixed Gaussian distribution model.
ID2image: Leakage of non-ID information into face descriptors and inversion from descriptors to images
Information about the environment (such as background and lighting) or changeable aspects of the face (such as pose, expression, presence of glasses, hat etc.)
