Aixuan Li

Orcid: 0009-0000-6868-2384

According to our database1, Aixuan Li authored at least 16 papers between 2020 and 2025.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2025
The Meeseeks Mesh: Spatially Consistent 3D Adversarial Objects for BEV Detector.
CoRR, May, 2025

Generative Transformer for Accurate and Reliable Salient Object Detection.
IEEE Trans. Circuits Syst. Video Technol., February, 2025

Enzyme Repertoires and Genomic Insights into <i>Lycium barbarum</i> Pectin Polysaccharide Biosynthesis.
Genom. Proteom. Bioinform., 2025

2024
Mutual Information Regularization for Weakly-Supervised RGB-D Salient Object Detection.
IEEE Trans. Circuits Syst. Video Technol., January, 2024

A Generative Victim Model for Segmentation.
CoRR, 2024

2023
Toward Deeper Understanding of Camouflaged Object Detection.
IEEE Trans. Circuits Syst. Video Technol., July, 2023

Joint Salient Object Detection and Camouflaged Object Detection via Uncertainty-aware Learning.
CoRR, 2023

Fine-grained Audible Video Description.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Semi-supervised Active Salient Object Detection.
Pattern Recognit., 2022

Towards Deeper Understanding of Camouflaged Object Detection.
CoRR, 2022

2021
Depth-Guided Camouflaged Object Detection.
CoRR, 2021

Transformer Transforms Salient Object Detection and Camouflaged Object Detection.
CoRR, 2021

Simultaneously Localize, Segment and Rank the Camouflaged Objects.
CoRR, 2021

Simultaneously Localize, Segment and Rank the Camouflaged Objects.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Uncertainty-Aware Joint Salient Object and Camouflaged Object Detection.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020
Weakly-Supervised Salient Object Detection via Scribble Annotations.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020


  Loading...