|
Haiyang Xu ο½ εΎζ΅·ι³ Hi! I am a Ph.D student at UC San Diego since Fall 2024, supervised by Prof. Zhuowen Tu. My current research focus is on computer vision and multimodal, especially on topics such as generative models and 3D vision. I am currently a research intern at NYU Courant, working with Prof. Saining Xie on generative models. Feel free to drop me an email to dicuss anything about research, life, and ourselves! Email / Scholar / X (Twitter) / Github |
|
News
[2024.06] π Our work FeatureMixture is finally accepted by TIP 2024! π |
Publications |
|
Bayesian Diffusion Models for 3D Shape Reconstruction
Haiyang Xu*, Yu Lei*, Zeyuan Chen, Xiang Zhang, Yue Zhao, Yilin Wang, Zhuowen Tu CVPR, 2024 project page / paper / code We propose Bayesian Diffusion Model (BDM) for 3D shape reconstruction, which performs effective Bayesian inference by tightly coupling the top-down (prior) information with the bottom-up procedure via joint diffusion processes. |
|
OmniControlNet: Dual-stage Integration for Conditional Image Generation
Yilin Wang*, Haiyang Xu*, Xiang Zhang, Zeyuan Chen, Zhizhou Sha, Zirui Wang, Zhuowen Tu CVPR Workshop, 2024 paper We propose OmniControlNet, a dual-stage integration framework for conditional image generation, which could effectively generate different controls and corresponding images in a unified framework. |
|
Feature Mixture on Pre-Trained Model for Few-Shot
Learning
Shuo Wang, Jinda Lu, Haiyang Xu, Yanbin Hao, Xiangnan He TIP, 2024 We propose a new feature mixture mechanism to improve the context extraction ability of the pre-trained model for few-shot learning. |
Great template from Jon Barron.