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Found 6 papers, 2 papers with code
WildGS-SLAM: Monocular Gaussian Splatting SLAM in Dynamic Environments
We present WildGS-SLAM, a robust and efficient monocular RGB SLAM system designed to handle dynamic environments by leveraging uncertainty-aware geometric mapping.
False Discovery Rate Control via Frequentist-assisted Horseshoe
The horseshoe prior, a widely used handy alternative to the spike-and-slab prior, has proven to be an exceptional default global-local shrinkage prior in Bayesian inference and machine learning.
NeRF On-the-go: Exploiting Uncertainty for Distractor-free NeRFs in the Wild
Neural Radiance Fields (NeRFs) have shown remarkable success in synthesizing photorealistic views from multi-view images of static scenes, but face challenges in dynamic, real-world environments with distractors like moving objects, shadows, and lighting changes.
NICER-SLAM: Neural Implicit Scene Encoding for RGB SLAM
Neural implicit representations have recently become popular in simultaneous localization and mapping (SLAM), especially in dense visual SLAM.
Hybrid Mesh-neural Representation for 3D Transparent Object Reconstruction
We propose a novel method to reconstruct the 3D shapes of transparent objects using hand-held captured images under natural light conditions.
NICE-SLAM: Neural Implicit Scalable Encoding for SLAM
Neural implicit representations have recently shown encouraging results in various domains, including promising progress in simultaneous localization and mapping (SLAM).
