Xiang Gao

According to our database, Xiang Gao authored at least 21 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Self-supervised Multi-view Learning via Auto-encoding 3D Transformations.

Xiang Gao, Wei Hu, Guo-Jun Qi

ACM Trans. Multim. Comput. Commun. Appl., January, 2024

Generative 3D Part Assembly via Part-Whole-Hierarchy Message Passing.

Bi'an Du, Xiang Gao, Wei Hu, Renjie Liao

CoRR, 2024

FBSDiff: Plug-and-Play Frequency Band Substitution of Diffusion Features for Highly Controllable Text-Driven Image Translation.

Xiang Gao, Jiaying Liu

Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

InvariantOODG: Learning Invariant Features of Point Clouds for Out-of-Distribution Generalization.

Zhimin Zhang, Xiang Gao, Wei Hu

Proceedings of the IEEE International Conference on Acoustics, 2024

Frequency-Controlled Diffusion Model for Versatile Text-Guided Image-to-Image Translation.

Xiang Gao, Zhengbo Xu, Junhan Zhao, Jiaying Liu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Self-Supervised Graph Representation Learning via Topology Transformations.

Xiang Gao, Wei Hu, Guo-Jun Qi

IEEE Trans. Knowl. Data Eng., April, 2023

Robust Graph-Based Segmentation of Noisy Point Clouds.

Pufan Li, Xiang Gao, Qianjiang Hu, Wei Hu

Proceedings of the IEEE International Conference on Image Processing, 2023

2022

Learning Latent Part-Whole Hierarchies for Point Clouds.

Xiang Gao, Wei Hu, Renjie Liao

CoRR, 2022

2021

Dynamic Point Cloud Denoising via Manifold-to-Manifold Distance.

Wei Hu, Qianjiang Hu, Zehua Wang, Xiang Gao

IEEE Trans. Image Process., 2021

Self-Contrastive Learning with Hard Negative Sampling for Self-supervised Point Cloud Learning.

Bi'an Du, Xiang Gao, Wei Hu, Xin Li

Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

Unsupervised Learning of Geometric Sampling Invariant Representations for 3D Point Clouds.

Haolan Chen, Shitong Luo, Xiang Gao, Wei Hu

Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

RGLN: Robust Residual Graph Learning Networks via Similarity-Preserving Mapping on Graphs.

Jiaxiang Tang, Xiang Gao, Wei Hu

Proceedings of the IEEE International Conference on Acoustics, 2021

2020

Feature Graph Learning for 3D Point Cloud Denoising.

Wei Hu, Xiang Gao, Gene Cheung, Zongming Guo

IEEE Trans. Signal Process., 2020

3D Dynamic Point Cloud Denoising via Spatial-Temporal Graph Learning.

Wei Hu, Qianjiang Hu, Zehua Wang, Xiang Gao

CoRR, 2020

Exploring Structure-Adaptive Graph Learning for Robust Semi-Supervised Classification.

Xiang Gao, Wei Hu, Zongming Guo

Proceedings of the IEEE International Conference on Multimedia and Expo, 2020

GraphTER: Unsupervised Learning of Graph Transformation Equivariant Representations via Auto-Encoding Node-Wise Transformations.

Xiang Gao, Wei Hu, Guo-Jun Qi

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Joint Learning of Graph Representation and Node Features in Graph Convolutional Neural Networks.

Jiaxiang Tang, Wei Hu, Xiang Gao, Zongming Guo

CoRR, 2019

3D Dynamic Point Cloud Denoising via Spatio-temporal Graph Modeling.

Qianjiang Hu, Zehua Wang, Wei Hu, Xiang Gao, Zongming Guo

CoRR, 2019

Exploring Graph Learning for Semi-Supervised Classification Beyond Euclidean Data.

Xiang Gao, Wei Hu, Zongming Guo

CoRR, 2019

Optimized Skeleton-based Action Recognition via Sparsified Graph Regression.

Xiang Gao, Wei Hu, Jiaxiang Tang, Jiaying Liu, Zongming Guo

Proceedings of the 27th ACM International Conference on Multimedia, 2019

2018

Generalized Graph Convolutional Networks for Skeleton-based Action Recognition.

Xiang Gao, Wei Hu, Jiaxiang Tang, Pan Pan, Jiaying Liu, Zongming Guo

CoRR, 2018