Wei Hu
98 papers · 2008–2026 · 17 venues · across top CS/AI venues
This profile combines several different researchers. Authors are keyed by name, and this name's papers fall into 22 separate collaboration groups - the largest holds only 27% of them. Pick the group below that matches the researcher you mean. How a shared name is split.
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Which Wei Hu?
14 groups of papers that share co-authors internally but none with each other - each most likely a different researcher. Pick one to see its papers.
with Daizong Liu, Qianjiang Hu, Xiang Gao
12 papers
· 2020–2026
· CVPR, AAAI, ICCV
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Spatial-Spectral Homogeneous Attacks on Physical-World Large Vision-Language Models
AAAI 2026
Large Scene Generation with Cube-Absorb Discrete Diffusion
ICCV 2025
Seeing is Not Believing: Adversarial Natural Object Optimization for Hard-Label 3D Scene Attacks
CVPR 2025
Explicitly Perceiving and Preserving the Local Geometric Structures for 3D Point Cloud Attack
AAAI 2024
Generative 3D Part Assembly via Part-Whole-Hierarchy Message Passing
CVPR 2024
RangeLDM: Fast Realistic LiDAR Point Cloud Generation
ECCV 2024
3DHacker: Spectrum-based Decision Boundary Generation for Hard-label 3D Point Cloud Attack
ICCV 2023
Density-Insensitive Unsupervised Domain Adaption on 3D Object Detection
CVPR 2023
Exploring the Devil in Graph Spectral Domain for 3D Point Cloud Attacks
ECCV 2022
Learning to Focus on the Foreground for Temporal Sentence Grounding
COLING 2022
AdCo: Adversarial Contrast for Efficient Learning of Unsupervised Representations From Self-Trained Negative Adversaries
CVPR 2021
GraphTER: Unsupervised Learning of Graph Transformation Equivariant Representations via Auto-Encoding Node-Wise Transformations
CVPR 2020
8 papers whose co-authors appear nowhere else under this name
Skill-Aware Data Selection and Fine-Tuning for Data-Efficient Reasoning Distillation
ACL 2026
DHGCN: Dynamic Hop Graph Convolution Network for Self-Supervised Point Cloud Learning
AAAI 2024
How Do Transformers Learn In-Context Beyond Simple Functions? A Case Study on Learning with Representations
ICLR 2024
Understanding Surprising Generalization Phenomena in Deep Learning
AAAI 2024
A Representation Learning Perspective on the Importance of Train-Validation Splitting in Meta-Learning
ICML 2021
Global-to-Local Neural Networks for Document-Level Relation Extraction
EMNLP 2020
Combinatorial Multi-Armed Bandit with General Reward Functions
NeurIPS 2016
Modeling Chinese Documents with Topical Word-Character Models
COLING 2008