Xiaoman Lu

Orcid: 0000-0003-0669-8780

According to our database1, Xiaoman Lu authored at least 12 papers between 2016 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Why Learn What Physics Already Knows? Realizing Agile mmWave-based Human Pose Estimation via Physics-Guided Preprocessing.
CoRR, March, 2026

Keeping the Evidence Chain: Semantic Evidence Allocation for Training-Free Token Pruning in Video Temporal Grounding.
CoRR, March, 2026

Towards Mitigating Modality Bias in Vision-Language Models for Temporal Action Localization.
CoRR, January, 2026

2025
RLAIF-V: Open-Source AI Feedback Leads to Super GPT-4V Trustworthiness.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024
PD-LL-Transformer: An Hourly PM2.5 Forecasting Method over the Yangtze River Delta Urban Agglomeration, China.
Remote. Sens., June, 2024

RLAIF-V: Aligning MLLMs through Open-Source AI Feedback for Super GPT-4V Trustworthiness.
CoRR, 2024

Contrastive Disentangled Representation Learning for Debiasing Recommendation with Uniform Data.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2022
Facial image inpainting for big data using an effective attention mechanism and a convolutional neural network.
Frontiers Neurorobotics, September, 2022

2021
Detection of Fire Smoke Plumes Based on Aerosol Scattering Using VIIRS Data over Global Fire-Prone Regions.
Remote. Sens., 2021

2017
Localization or Globalization? Determination of the Optimal Regression Window for Disaggregation of Land Surface Temperature.
IEEE Trans. Geosci. Remote. Sens., 2017

Combining Multi-Source Remotely Sensed Data and a Process-Based Model for Forest Aboveground Biomass Updating.
Sensors, 2017

2016
Assessing the effects of understory to forest canopy leaf area index by combining moderate resolution data and geometric optical (GO) model in temperate forest.
Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium, 2016


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