Institution profile

Université de Picardie Jules Verne

Academic institutioneurope · fr
Official website
Research library40linked papers
Opportunities0open roles
Selected work

Representative Papers

A Height-Constrained 2-Point Minimal Solver for Pose Estimation from Active LED Markers with Event Cameras

Aug 10, 2026

This work addresses the challenge of pose estimation in space-constrained environments, where conventional multi-point PnP methods are difficult to deploy and fail to exploit available ego-motion priors such as known height and tilt angle. The authors propose a minimal pose solver requiring only two active LED markers, uniquely incorporating height and tilt constraints into a two-point geometric model. They derive both a closed-form solution and a linear least-squares formulation, and provide a systematic analysis of degenerate configurations. By fusing event camera data with IMU and altimeter measurements within the proposed geometric framework, the method significantly outperforms existing P2P approaches on both synthetic and real-world datasets, achieving accuracy comparable to P3P while demonstrating superior efficiency, accuracy, and robustness.

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ED-CSP: Crystal Structure Prediction from Electron Diffraction

Aug 06, 2026

Reconstructing three-dimensional crystal structures from sparse, uncalibrated electron diffraction (ED) data poses a highly challenging generative inverse problem. This work proposes ED-CSP, the first framework capable of end-to-end crystal structure generation using only sparse multi-view ED spots, without requiring diffraction calibration, label prediction, or database retrieval. By incorporating chemical composition and atomic counts, ED-CSP jointly predicts lattice parameters and fractional atomic coordinates through a relational set encoder, a permutation-invariant multi-view aggregator, and a periodic flow generator. On the CHILI-100K benchmark, it achieves an MR@5 of 57.49%, improving to 66.27% with expanded training data; notably, it maintains strong performance on out-of-distribution compositions with an MR@5 of 53.52%, substantially outperforming PXRDGen and demonstrating both genuine generative capability and robust generalization.

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Recent publications

Latest Papers

A Height-Constrained 2-Point Minimal Solver for Pose Estimation from Active LED Markers with Event Cameras

Aug 10, 2026

This work addresses the challenge of pose estimation in space-constrained environments, where conventional multi-point PnP methods are difficult to deploy and fail to exploit available ego-motion priors such as known height and tilt angle. The authors propose a minimal pose solver requiring only two active LED markers, uniquely incorporating height and tilt constraints into a two-point geometric model. They derive both a closed-form solution and a linear least-squares formulation, and provide a systematic analysis of degenerate configurations. By fusing event camera data with IMU and altimeter measurements within the proposed geometric framework, the method significantly outperforms existing P2P approaches on both synthetic and real-world datasets, achieving accuracy comparable to P3P while demonstrating superior efficiency, accuracy, and robustness.

0 citationsRead paper

ED-CSP: Crystal Structure Prediction from Electron Diffraction

Aug 06, 2026

Reconstructing three-dimensional crystal structures from sparse, uncalibrated electron diffraction (ED) data poses a highly challenging generative inverse problem. This work proposes ED-CSP, the first framework capable of end-to-end crystal structure generation using only sparse multi-view ED spots, without requiring diffraction calibration, label prediction, or database retrieval. By incorporating chemical composition and atomic counts, ED-CSP jointly predicts lattice parameters and fractional atomic coordinates through a relational set encoder, a permutation-invariant multi-view aggregator, and a periodic flow generator. On the CHILI-100K benchmark, it achieves an MR@5 of 57.49%, improving to 66.27% with expanded training data; notably, it maintains strong performance on out-of-distribution compositions with an MR@5 of 53.52%, substantially outperforming PXRDGen and demonstrating both genuine generative capability and robust generalization.

0 citationsRead paper