Xiang Yu

papers

610

total citations

papers (15)

Q: How To Specialize Large Vision-Language Models to Data-Scarce VQA Tasks? A: Self-Train on Unlabeled Images!

CVPR 2023arXiv

citations

Single-Stream Multi-level Alignment for Vision-Language Pretraining

ECCV 2022arXiv

citations

Improving Face Recognition by Clustering Unlabeled Faces in the Wild

ECCV 2020arXiv

citations

DeFormer: Integrating Transformers with Deformable Models for 3D Shape Abstraction from a Single Image

ICCV 2023arXiv

citations

Domain Generalization Guided by Gradient Signal to Noise Ratio of Parameters

ICCV 2023arXiv

citations

Revisiting Source-Free Domain Adaptation: Insights into Representativeness, Generalization, and Variety

CVPR 2025

citations

Learning To Learn Across Diverse Data Biases in Deep Face Recognition

CVPR 2022

citations

Learning Phase Mask for Privacy-Preserving Passive Depth Estimation

ECCV 2022

citations

Private-kNN: Practical Differential Privacy for Computer Vision

CVPR 2020

citations

Xiang Yu

papers (15)

Selective Structured State-Spaces for Long-Form Video Understanding

Towards Universal Representation Learning for Deep Face Recognition

Learning Cross-Modal Contrastive Features for Video Domain Adaptation

On Generalizing Beyond Domains in Cross-Domain Continual Learning

Controllable Dynamic Multi-Task Architectures

Cross-Domain Similarity Learning for Face Recognition in Unseen Domains

Q: How To Specialize Large Vision-Language Models to Data-Scarce VQA Tasks? A: Self-Train on Unlabeled Images!

Single-Stream Multi-level Alignment for Vision-Language Pretraining

Improving Face Recognition by Clustering Unlabeled Faces in the Wild

DeFormer: Integrating Transformers with Deformable Models for 3D Shape Abstraction from a Single Image

Domain Generalization Guided by Gradient Signal to Noise Ratio of Parameters

Revisiting Source-Free Domain Adaptation: Insights into Representativeness, Generalization, and Variety

Learning To Learn Across Diverse Data Biases in Deep Face Recognition

Learning Phase Mask for Privacy-Preserving Passive Depth Estimation

Private-kNN: Practical Differential Privacy for Computer Vision

papers (15)

Selective Structured State-Spaces for Long-Form Video Understanding

Towards Universal Representation Learning for Deep Face Recognition

Learning Cross-Modal Contrastive Features for Video Domain Adaptation

On Generalizing Beyond Domains in Cross-Domain Continual Learning

Controllable Dynamic Multi-Task Architectures

Cross-Domain Similarity Learning for Face Recognition in Unseen Domains

Q: How To Specialize Large Vision-Language Models to Data-Scarce VQA Tasks? A: Self-Train on Unlabeled Images!

Single-Stream Multi-level Alignment for Vision-Language Pretraining

Improving Face Recognition by Clustering Unlabeled Faces in the Wild

DeFormer: Integrating Transformers with Deformable Models for 3D Shape Abstraction from a Single Image

Domain Generalization Guided by Gradient Signal to Noise Ratio of Parameters

Revisiting Source-Free Domain Adaptation: Insights into Representativeness, Generalization, and Variety

Learning To Learn Across Diverse Data Biases in Deep Face Recognition

Learning Phase Mask for Privacy-Preserving Passive Depth Estimation

Private-kNN: Practical Differential Privacy for Computer Vision