Zechuan Li

According to our database1, Zechuan Li authored at least 14 papers between 2023 and 2025.

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

Timeline

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Bibliography

2025
A Survey on MLLM-based Visually Rich Document Understanding: Methods, Challenges, and Emerging Trends.
CoRR, July, 2025

PointDiffuse: A Dual-Conditional Diffusion Model for Enhanced Point Cloud Semantic Segmentation.
CoRR, March, 2025

A Training-Free Length Extrapolation Approach for LLMs: Greedy Attention Logit Interpolation (GALI).
CoRR, February, 2025

Embodied Intelligence for 3D Understanding: A Survey on 3D Scene Question Answering.
CoRR, February, 2025

Beyond Full Labels: Energy-Double-Guided Single-Point Prompt for Infrared Small Target Label Generation.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2025

GO-N3RDet: Geometry Optimized NeRF-enhanced 3D Object Detector.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024
EFRNet-VL: An end-to-end feature refinement network for monocular visual localization in dynamic environments.
Expert Syst. Appl., 2024

DAViD: Domain Adaptive Visually-Rich Document Understanding with Synthetic Insights.
CoRR, 2024

Beyond Full Label: Single-Point Prompt for Infrared Small Target Label Generation.
CoRR, 2024

MVDetector: Malicious Vehicles Detection Under Sybil Attacks in VANETs.
Proceedings of the Information Security - 27th International Conference, 2024

OST: Refining Text Knowledge with Optimal Spatio-Temporal Descriptor for General Video Recognition.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Improved MLP Point Cloud Processing with High-Dimensional Positional Encoding.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
First Place Solution to the CVPR'2023 AQTC Challenge: A Function-Interaction Centric Approach with Spatiotemporal Visual-Language Alignment.
CoRR, 2023

AShapeFormer : Semantics-Guided Object-Level Active Shape Encoding for 3D Object Detection via Transformers.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023


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