A method fuses DAS strain-rate data from traffic with vehicle trajectories to optimize fiber geometry estimates, achieving sub-meter accuracy in simulations and field tests.
Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography
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A neural network performs simultaneous static-moving segmentation and ego-motion estimation directly from raw radar point clouds using MLPs and RNNs.
Real2Sim reconstructs editable dynamic driving scenes as temporally continuous Gaussians integrated with a differentiable MPM physics solver for high-fidelity simulation of interactions and collisions.
Angle-I2P rejects outliers in cross-modality registration via scale-invariant angular consistency and hierarchical attention, reporting state-of-the-art inlier ratio and registration recall on 7Scenes, RGBD Scenes V2, and a self-collected dataset.
DualReg filters feature matches with one-point RANSAC then refines via geometric proxies to achieve 32x CPU speedup over MAC on KITTI while maintaining comparable accuracy.
DeepDetect trains ESPNet on fused classical detector masks to produce dense, repeatable keypoints that outperform prior methods on Oxford, HPatches, and Middlebury benchmarks.
citing papers explorer
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Buried Fiber-Optic Geolocalization with Distributed Acoustic Sensing
A method fuses DAS strain-rate data from traffic with vehicle trajectories to optimize fiber geometry estimates, achieving sub-meter accuracy in simulations and field tests.
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Redefining Radar Segmentation: Simultaneous Static-Moving Segmentation and Ego-Motion Estimation using Radar Point Clouds
A neural network performs simultaneous static-moving segmentation and ego-motion estimation directly from raw radar point clouds using MLPs and RNNs.
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Real2Sim: A Physics-driven and Editable Gaussian Splatting Framework for Autonomous Driving Scenes
Real2Sim reconstructs editable dynamic driving scenes as temporally continuous Gaussians integrated with a differentiable MPM physics solver for high-fidelity simulation of interactions and collisions.
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Angle-I2P: Angle-Consistent-Aware Hierarchical Attention for Cross-Modality Outlier Rejection
Angle-I2P rejects outliers in cross-modality registration via scale-invariant angular consistency and hierarchical attention, reporting state-of-the-art inlier ratio and registration recall on 7Scenes, RGBD Scenes V2, and a self-collected dataset.
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DualReg: Dual-Space Filtering and Reinforcement for Rigid Registration
DualReg filters feature matches with one-point RANSAC then refines via geometric proxies to achieve 32x CPU speedup over MAC on KITTI while maintaining comparable accuracy.
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DeepDetect: Learning All-in-One Dense Keypoints
DeepDetect trains ESPNet on fused classical detector masks to produce dense, repeatable keypoints that outperform prior methods on Oxford, HPatches, and Middlebury benchmarks.