Xu Zheng

Orcid: 0000-0003-4008-8951

Affiliations:

AI Thrust, Hong Kong University of Science and Technology (HKUST), Guangzhou, China

According to our database¹, Xu Zheng authored at least 50 papers between 2022 and 2025.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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Bibliography

2025

Partial CLIP is Enough: Chimera-Seg for Zero-shot Semantic Segmentation.

[BibT_eX]

[DOI]

CoRR, June, 2025

Unlocking Constraints: Source-Free Occlusion-Aware Seamless Segmentation.

[BibT_eX]

[DOI]

CoRR, June, 2025

Domain-RAG: Retrieval-Guided Compositional Image Generation for Cross-Domain Few-Shot Object Detection.

[BibT_eX]

[DOI]

CoRR, June, 2025

BiXFormer: A Robust Framework for Maximizing Modality Effectiveness in Multi-Modal Semantic Segmentation.

[BibT_eX]

[DOI]

CoRR, June, 2025

Shifting AI Efficiency From Model-Centric to Data-Centric Compression.

[BibT_eX]

[DOI]

CoRR, May, 2025

Self-Supervised and Generalizable Tokenization for CLIP-Based 3D Understanding.

[BibT_eX]

[DOI]

CoRR, May, 2025

Manifold-aware Representation Learning for Degradation-agnostic Image Restoration.

[BibT_eX]

[DOI]

CoRR, May, 2025

MLLMs are Deeply Affected by Modality Bias.

[BibT_eX]

[DOI]

CoRR, May, 2025

Are Multimodal Large Language Models Ready for Omnidirectional Spatial Reasoning?

[BibT_eX]

[DOI]

CoRR, May, 2025

Adversarial Robustness for Unified Multi-Modal Encoders via Efficient Calibration.

[BibT_eX]

[DOI]

CoRR, May, 2025

Reducing Unimodal Bias in Multi-Modal Semantic Segmentation with Multi-Scale Functional Entropy Regularization.

[BibT_eX]

[DOI]

CoRR, May, 2025

Split Matching for Inductive Zero-shot Semantic Segmentation.

[BibT_eX]

[DOI]

CoRR, May, 2025

Retrieval Augmented Generation and Understanding in Vision: A Survey and New Outlook.

[BibT_eX]

[DOI]

CoRR, March, 2025

OmniSAM: Omnidirectional Segment Anything Model for UDA in Panoramic Semantic Segmentation.

[BibT_eX]

[DOI]

CoRR, March, 2025

MemorySAM: Memorize Modalities and Semantics with Segment Anything Model 2 for Multi-modal Semantic Segmentation.

[BibT_eX]

[DOI]

CoRR, March, 2025

Unveiling the Potential of Segment Anything Model 2 for RGB-Thermal Semantic Segmentation with Language Guidance.

[BibT_eX]

[DOI]

CoRR, March, 2025

360SFUDA++: Towards Source-Free UDA for Panoramic Segmentation by Learning Reliable Category Prototypes.

[BibT_eX]

[DOI]

Xu Zheng

Peng Yuan Zhou

Athanasios V. Vasilakos

Lin Wang

IEEE Trans. Pattern Anal. Mach. Intell., February, 2025

RealRAG: Retrieval-augmented Realistic Image Generation via Self-reflective Contrastive Learning.

[BibT_eX]

[DOI]

CoRR, February, 2025

Distilling efficient Vision Transformers from CNNs for semantic segmentation.

[BibT_eX]

[DOI]

Pattern Recognit., 2025

Benchmarking Multi-modal Semantic Segmentation under Sensor Failures: Missing and Noisy Modality Robustness.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2025

A Survey of Mathematical Reasoning in the Era of Multimodal Large Language Model: Benchmark, Method & Challenges.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics, 2025

MMUnlearner: Reformulating Multimodal Machine Unlearning in the Era of Multimodal Large Language Models.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics, 2025

2024

Frozen is better than learning: A new design of prototype-based classifier for semantic segmentation.

[BibT_eX]

[DOI]

Pattern Recognit., 2024

MAGIC++: Efficient and Resilient Modality-Agnostic Semantic Segmentation via Hierarchical Modality Selection.

[BibT_eX]

[DOI]

CoRR, 2024

A Survey of Mathematical Reasoning in the Era of Multimodal Large Language Model: Benchmark, Method & Challenges.

[BibT_eX]

[DOI]

CoRR, 2024

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation.

[BibT_eX]

[DOI]

CoRR, 2024

EIT-1M: One Million EEG-Image-Text Pairs for Human Visual-textual Recognition and More.

[BibT_eX]

[DOI]

CoRR, 2024

OmniBind: Teach to Build Unequal-Scale Modality Interaction for Omni-Bind of All.

[BibT_eX]

[DOI]

CoRR, 2024

GoodSAM: Bridging Domain and Capacity Gaps via Segment Anything Model for Distortion-aware Panoramic Semantic Segmentation.

[BibT_eX]

[DOI]

CoRR, 2024

EventDance: Unsupervised Source-free Cross-modal Adaptation for Event-based Object Recognition.

[BibT_eX]

[DOI]

Xu Zheng

Lin Wang

CoRR, 2024

ExACT: Language-guided Conceptual Reasoning and Uncertainty Estimation for Event-based Action Recognition and More.

[BibT_eX]

[DOI]

CoRR, 2024

UniBind: LLM-Augmented Unified and Balanced Representation Space to Bind Them All.

[BibT_eX]

[DOI]

CoRR, 2024

Image Anything: Towards Reasoning-coherent and Training-free Multi-modal Image Generation.

[BibT_eX]

[DOI]

Yuanhuiyi Lyu

Xu Zheng

Lin Wang

CoRR, 2024

Chasing Day and Night: Towards Robust and Efficient All-Day Object Detection Guided by an Event Camera.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Transformer-CNN Cohort: Semi-supervised Semantic Segmentation by the Best of Both Students.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

EventBind: Learning a Unified Representation to Bind Them All for Event-Based Open-World Understanding.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2024, 2024

Centering the Value of Every Modality: Towards Efficient and Resilient Modality-Agnostic Semantic Segmentation.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2024, 2024

Learning Modality-Agnostic Representation for Semantic Segmentation from Any Modalities.

[BibT_eX]

[DOI]

Xu Zheng

Yuanhuiyi Lyu

Lin Wang

Proceedings of the Computer Vision - ECCV 2024, 2024

Semantics, Distortion, and Style Matter: Towards Source-Free UDA for Panoramic Segmentation.

[BibT_eX]

[DOI]

Xu Zheng

Pengyuan Zhou

Athanasios V. Vasilakos

Lin Wang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Adversarial co-training for semantic segmentation over medical images.

[BibT_eX]

[DOI]

Comput. Biol. Medicine, May, 2023

CLIP Is Also a Good Teacher: A New Learning Framework for Inductive Zero-shot Semantic Segmentation.

[BibT_eX]

[DOI]

CoRR, 2023

E-CLIP: Towards Label-efficient Event-based Open-world Understanding by CLIP.

[BibT_eX]

[DOI]

CoRR, 2023

Deep Learning for Event-based Vision: A Comprehensive Survey and Benchmarks.

[BibT_eX]

[DOI]

CoRR, 2023

A Good Student is Cooperative and Reliable: CNN-Transformer Collaborative Learning for Semantic Segmentation.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Look at the Neighbor: Distortion-aware Unsupervised Domain Adaptation for Panoramic Semantic Segmentation.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Both Style and Distortion Matter: Dual-Path Unsupervised Domain Adaptation for Panoramic Semantic Segmentation.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Transformer-CNN Cohort: Semi-supervised Semantic Segmentation by the Best of Both Students.

[BibT_eX]

[DOI]

CoRR, 2022

All One Needs to Know about Priors for Deep Image Restoration and Enhancement: A Survey.

[BibT_eX]

[DOI]

CoRR, 2022

Uncertainty-aware deep co-training for semi-supervised medical image segmentation.

[BibT_eX]

[DOI]

Comput. Biol. Medicine, 2022

Uncertainty teacher with dense focal loss for semi-supervised medical image segmentation.

[BibT_eX]

[DOI]

Comput. Biol. Medicine, 2022

Xu Zheng

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