Jialei Xu

Orcid: 0000-0002-5298-6057

According to our database1, Jialei Xu authored at least 18 papers between 2021 and 2026.

Collaborative distances:

Timeline

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Bibliography

2026
Clinical-Prior Guided Multi-Modal Learning with Latent Attention Pooling for Gait-Based Scoliosis Screening.
CoRR, February, 2026

Token Entropy Regularization for Multi-modal Antenna Affiliation Identification.
CoRR, January, 2026

2025
SpaceMind: Camera-Guided Modality Fusion for Spatial Reasoning in Vision-Language Models.
CoRR, November, 2025

CitySeg: A 3D Open Vocabulary Semantic Segmentation Foundation Model in City-scale Scenarios.
CoRR, August, 2025

Self-Supervised Multi-Camera Collaborative Depth Prediction With Latent Diffusion Models.
IEEE Trans. Intell. Transp. Syst., July, 2025

Unveiling the Depths: A Multi-Modal Fusion Framework for Challenging Scenarios.
Proceedings of the IEEE International Conference on Robotics and Automation, 2025


2024
Adaptive Stereo Depth Estimation with Multi-Spectral Images Across All Lighting Conditions.
CoRR, 2024

DINO-SD: Champion Solution for ICRA 2024 RoboDepth Challenge.
CoRR, 2024

The RoboDrive Challenge: Drive Anytime Anywhere in Any Condition.
CoRR, 2024

Unveiling the Depths: A Multi-Modal Fusion Framework for Challenging Scenarios.
CoRR, 2024

SDGE: Stereo Guided Depth Estimation for 360°Camera Sets.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2024

2022
Multi-Camera Collaborative Depth Prediction via Consistent Structure Estimation.
Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

LiteDepth: Digging into Fast and Accurate Depth Estimation on Mobile Devices.
Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022


2021
Weakly-Supervised Monocular Depth Estimationwith Resolution-Mismatched Data.
CoRR, 2021

Fast and Accurate Single-Image Depth Estimation on Mobile Devices, Mobile AI 2021 Challenge: Report.
CoRR, 2021

A many-objective optimized task allocation scheduling model in cloud computing.
Appl. Intell., 2021


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