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Found 6 papers, 3 papers with code
PSS-BA: LiDAR Bundle Adjustment with Progressive Spatial Smoothing
The proposed method consists of a spatial smoothing module and a pose adjustment module, which combines the benefits of local consistency and global accuracy.
MMAUD: A Comprehensive Multi-Modal Anti-UAV Dataset for Modern Miniature Drone Threats
In response to the evolving challenges posed by small unmanned aerial vehicles (UAVs), which possess the potential to transport harmful payloads or independently cause damage, we introduce MMAUD: a comprehensive Multi-Modal Anti-UAV Dataset.
DeepAAT: Deep Automated Aerial Triangulation for Fast UAV-based Mapping
The experimental results demonstrate DeepAAT's substantial improvements over conventional AAT methods, highlighting its potential in the efficiency and accuracy of UAV-based 3D reconstruction tasks.
Mobile-Seed: Joint Semantic Segmentation and Boundary Detection for Mobile Robots
Our framework features a two-stream encoder, an active fusion decoder (AFD) and a dual-task regularization approach.
CoFiI2P: Coarse-to-Fine Correspondences for Image-to-Point Cloud Registration
Specifically, In the coarse matching phase, a novel I2P transformer module is employed to capture both homogeneous and heterogeneous global information from the image and point cloud data.
Object-Aware Dense Semantic Correspondence
To address these problems, this paper proposes an object-aware method to estimate per-pixel correspondences from semantic to low-level by learning a classifier for each selected discriminative grid cell and guiding the localization of every pixel under the semantic constraint.
