Jiaxing Huang · Nanyang Technological University

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Works57 from public data

TitleCited by

Vision-Language Models for Vision Tasks: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence · 2024
1,668
FSDR: Frequency Space Domain Randomization for Domain Generalization
IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 2021
319
Transfer Learning from Synthetic to Real LiDAR Point Cloud for Semantic Segmentation
Proceedings of the AAAI Conference on Artificial Intelligence · 2022
169
Unsupervised Point Cloud Representation Learning With Deep Neural Networks: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence · 2023
156
Uncertainty-Aware Unsupervised Domain Adaptation in Object Detection
IEEE Transactions on Multimedia · 2021
151
Contextual-Relation Consistent Domain Adaptation for Semantic Segmentation
Lecture notes in computer science · 2020
133
Model Adaptation: Historical Contrastive Learning for Unsupervised Domain Adaptation without Source Data
arXiv · 2021
95
Foundation Models for Remote Sensing and Earth Observation: A survey
IEEE Geoscience and Remote Sensing Magazine · 2025
93
RDA: Robust Domain Adaptation via Fourier Adversarial Attacking
IEEE/CVF International Conference on Computer Vision (ICCV) · 2021
89
Spectral Unsupervised Domain Adaptation for Visual Recognition
IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 2022
88
Scale variance minimization for unsupervised domain adaptation in image segmentation
Pattern Recognition · 2020
71
Cross-View Regularization for Domain Adaptive Panoptic Segmentation
IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 2021
66
FPS-Net: A convolutional fusion network for large-scale LiDAR point cloud segmentation
ISPRS Journal of Photogrammetry and Remote Sensing · 2021
64
R1-ShareVL: Incentivizing Reasoning Capability of Multimodal Large Language Models via Share-GRPO
arXiv · 2025
59
LLMs Meet VLMs: Boost Open Vocabulary Object Detection with Fine-grained Descriptors
arXiv · 2024
57
Unbiased Subclass Regularization for Semi-Supervised Semantic Segmentation
IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 2022
57
Multi-level adversarial network for domain adaptive semantic segmentation
Pattern Recognition · 2021
51
Domain Adaptive Video Segmentation via Temporal Consistency Regularization
IEEE/CVF International Conference on Computer Vision (ICCV) · 2021
47
Software Project Risk Management Modeling with Neural Network and Support Vector Machine Approaches
International Conference on Natural Computation (ICNC) · 2007
42
Black-box Unsupervised Domain Adaptation with Bi-directional Atkinson-Shiffrin Memory
IEEE/CVF International Conference on Computer Vision (ICCV) · 2023
30
Domain Generalization via Balancing Training Difficulty and Model Capability
IEEE/CVF International Conference on Computer Vision (ICCV) · 2023
29
Image-to-Character-to-Word Transformers for Accurate Scene Text Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence · 2023
27
DA-DETR: Domain Adaptive Detection Transformer by Hybrid Attention
arXiv · 2021
27
MMReason: An Open-Ended Multi-Modal Multi-Step Reasoning Benchmark for MLLMs Toward AGI
IEEE/CVF International Conference on Computer Vision (ICCV) · 2025
19
D-LC-Nets: Robust Denoising and Loop Closing Networks for LiDAR SLAM in Complicated Circumstances with Noisy Point Clouds
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · 2022
19

Publication data from OpenAlex; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-10. Citation counts may be lower than on Google Scholar, which indexes more sources.

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