Xinran Qin

Orcid: 0000-0001-7145-5406

According to our database1, Xinran Qin authored at least 14 papers between 2021 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
YOSE: You Only Select Essential Tokens for Efficient DiT-based Video Object Removal.
CoRR, April, 2026

HP-Edit: A Human-Preference Post-Training Framework for Image Editing.
CoRR, April, 2026

Disentangle to Fuse: Toward Content Preservation and Cross-Modality Consistency for Multi-Modality Image Fusion.
IEEE Trans. Image Process., 2026

2025
Reinforced Diffusion: Learning to Push the Limits of Anisotropic Diffusion for Image Denoising.
CoRR, December, 2025

Robust Unsupervised Deep Learning for Nonblind Image Deconvolution With Inaccurate Kernels.
IEEE Trans. Neural Networks Learn. Syst., September, 2025

CamEdit: Continuous Camera Parameter Control for Photorealistic Image Editing.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

2024
Siamese Cooperative Learning for Unsupervised Image Reconstruction From Incomplete Measurements.
IEEE Trans. Pattern Anal. Mach. Intell., 2024

Enhanced deep unrolling networks for snapshot compressive hyperspectral imaging.
Neural Networks, 2024

2023
Towards Flexible, Scalable, and Adaptive Multi-Modal Conditioned Face Synthesis.
CoRR, 2023

Ground-Truth Free Meta-Learning for Deep Compressive Sampling.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Automated testing of image captioning systems.
Proceedings of the ISSTA '22: 31st ACM SIGSOFT International Symposium on Software Testing and Analysis, Virtual Event, South Korea, July 18, 2022

High-Quality Self-Supervised Snapshot Hyperspectral Imaging.
Proceedings of the IEEE International Conference on Acoustics, 2022

Dual-Domain Self-supervised Learning and Model Adaption for Deep Compressive Imaging.
Proceedings of the Computer Vision - ECCV 2022, 2022

2021
Dynamic fusion for ensemble of deep Q-network.
Int. J. Mach. Learn. Cybern., 2021


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