Tiange Xiang    向天戈

I am a CS Ph.D. student in Stanford Vision and Learning Lab (SVL).
I'm advised by Sequoia Capital Prof. Fei-Fei Li (computer science) and
co-advised by James H. Clark Prof. Scott Delp (biomechanics).

I received my Bachelor's degree from The University of Sydney, where I was fortunate to work with Prof. Weidong Cai. I was awarded Honors Class I and The University Medal.

I do research on AI & Computer Vision.

Contact: {X @ Y}, where X=xtiange, Y=stanford.edu

Google Scholar  /  Github  /  Linkedin

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Publications ( * indicates equal contributions)
Rendering Humans from Object-Occluded Monocular Videos
Tiange Xiang, Adam Sun, Jiajun Wu, Ehsan Adeli, and Li Fei-Fei
ICCV, 2023

We rendered human from object occluded videos.
[ paper  /  code ]
In-painting Radiography Images for Unsupervised Anomaly Detection
Tiange Xiang, Yixiao Zhang, Yongyi Lu, Alan L. Yuille, Chaoyi Zhang, Weidong Cai,
and Zongwei Zhou
CVPR, 2023

We re-formulated unsupervised anomaly detection as semantic-sapce in-painting.
[ paper  /  code ]
Seeing Beyond the Brain: Conditional Diffusion Model with Sparse Masked Modeling for Vision Decoding
Zijiao Chen*, Jiaxin Qing*, Tiange Xiang, Wan Lin Yue, and Juan Helen Zhou
CVPR, 2023

We decoded photo-realistic visual stimuli from fMRI brain signals.
[ project page  /  code  /  paper ]
DDM2: Self-Supervised Diffusion MRI Denoising with Generative Diffusion Models
Tiange Xiang, Mahmut Yurt, Ali B Syed, Kawin Setsompop, and Akshay Chaudhari
ICLR, 2023

We achieved self-supervised MRI denoising through generative diffusion models.
[ paper  /  code ]
Walk in the Cloud: Learning Curves for Point Clouds Shape Analysis
Tiange Xiang, Chaoyi Zhang, Yang Song, Jianhui Yu, and Weidong Cai
ICCV, 2021

We proposed a geometry-aware feature aggregation operator for point cloud analysis.
[ project page  /  paper  /  code ]
Towards Bi-directional Skip Connections in Encoder-Decoder Architectures and Beyond
Tiange Xiang, Chaoyi Zhang, Xinyi Wang, Yang Song, Dongnan Liu, Heng Huang,
and Weidong Cai
MedIA, 2022

An efficient and light-weight encoder-decoder network with SOTA performances.
[ project page  /  paper ]
BiX-NAS: Searching Efficient Bi-directional Architectures for Medical Image Segmentation
Xinyi Wang*, Tiange Xiang*, Chaoyi Zhang, Yang Song, Dongnan Liu, Heng Huang,
and Weidong Cai
MICCAI, 2021

We proposed a NAS method to search efficient bi-directional architectures.
[ project page  /  paper  /  code ]
BiO-Net: Learning Recurrent Bidirectional Connections for Encoder-Decoder Architecture
Tiange Xiang, Chaoyi Zhang, Dongnan Liu, Yang Song, Heng Huang,
and Weidong Cai
MICCAI, 2020

We proposed bi-directional skip connections in the encoder-decoder architecture.
[ project page  /  paper  /  code ]
DSNet: A Weakly-Supervised Dual-Stream Framework for Effective Gigapixel Pathology Image Analysis
Tiange Xiang, Yang Song, Chaoyi Zhang, Dongnan Liu, Mei Chen, Fan Zhang,
Heng Huang, Lauren O'Donnell, and Weidong Cai
TMI, 2022

We proposed to combine global-local clues for weakly-supervised WSI analysis.
[ paper ]
Partial Graph Reasoning for Neural Network Regularization
Tiange Xiang, Chaoyi Zhang, Yang Song, Siqi Liu, Hongliang Yuan, and Weidong Cai

We formulated regularization as generative distortions through learnable graphs.
[ project page  /  paper ]
Two-Stage Monte Carlo Denoising with Adaptive Sampling and Kernel Pool
Tiange Xiang, Hongliang Yuan, Haozhi Huang, and Yujin Shi

We achieved real-time denoising for online rendering at adaptive spp counts
[ paper ]
  • Conference reviewer for CVPR(2021,2022,2023), MICCAI(2021, 2022, 2023), ICCV 2023, ICML 2022, ECCV 2022, NeurIPS 2022, WACV 2023.
  • Journal reviewer for IEEE TPAMI, IEEE TMI, Neurocomputing.

  • Last updated on 01/09/2023;     Template from here