[Tiange :)]
Tiange Xiang 向天戈
Ph.D. Student, Stanford Vision and Learning Lab
Contact: {X @ Y}, X=xtiange, Y=stanford.edu
Tiange Xiang (向天戈) is a second-year CS Ph.D. student at Stanford University. He is affiliated with Stanford AI Lab & Stanford Vision and Learning Lab. He is advised by Prof. Fei-Fei Li, co-advised by Prof. Scott Delp and Prof. Ehsan Adeli. Previously, he worked with Prof. Weidong Cai at The University of Sydney, where he was awarded Honors Class I and The University Medal. His research focuses on 3D computer vision & AI for healthcare.

Family name: (Xiàng) means the direction.

Given name: (Tiān) () means the weapon from the heavenly realm.

Selected Conference Publications
[* indicates equal contribution]
Rendering Humans from Object-Occluded Monocular Videos
Tiange Xiang, Adam Sun, Jiajun Wu, Ehsan Adeli, and Li Fei-Fei
We rendered human from object occluded videos.
SQUID: Deep Feature In-Painting for Unsupervised Anomaly Detection
We re-formulated unsupervised anomaly detection as semantic-sapce in-painting.
Seeing Beyond the Brain: Conditional Diffusion Model with Sparse Masked Modeling for Vision Decoding
We decoded photo-realistic visual stimuli from fMRI brain signals.
DDM2: Self-Supervised Diffusion MRI Denoising with Generative Diffusion Models
We achieved self-supervised MRI denoising through generative diffusion models.
Walk in the Cloud: Learning Curves for Point Clouds Shape Analysis
We proposed a geometry-aware feature aggregation operator for point cloud analysis.
BiX-NAS: Searching Efficient Bi-directional Architectures for Medical Image Segmentation
We proposed a NAS method to search efficient bi-directional architectures.
BiO-Net: Learning Recurrent Bidirectional Connections for Encoder-Decoder Architecture
We proposed bi-directional skip connections in the encoder-decoder architecture.
Journal Publications
[* indicates equal contribution]
Exploiting Structural Consistency of Chest Anatomy for Unsupervised Anomaly Detection in Radiography Images
A faster and stronger network for chest X-ray anomaly detection.
Towards Bi-directional Skip Connections in Encoder-Decoder Architectures and Beyond
An efficient and light-weight encoder-decoder network with SOTA performances.
DSNet: A Weakly-Supervised Dual-Stream Framework for Effective Gigapixel Pathology Image Analysis
We proposed to combine global-local clues for weakly-supervised WSI analysis.
[* indicates equal contribution]
Partial Graph Reasoning for Neural Network Regularization
Tiange Xiang, Chaoyi Zhang, Yang Song, Siqi Liu, Hongliang Yuan, and Weidong Cai
Two-Stage Monte Carlo Denoising with Adaptive Sampling and Kernel Pool
Tiange Xiang, Hongliang Yuan, Haozhi Huang, and Yujin Shi
Ph.D. Student in Computer Science
Palo Alto, CA, U.S.
B.S. in Computer Science and Technology (Advanced) (Honours)
Sydney, NSW, Australia
July. 2022
Conference reviewer:
CVPR (2021,2022,2023,2024), MICCAI (2021,2022,2023,2024), ICCV 2023, ICML 2022, ECCV (2022,2024), NeurIPS 2022, WACV 2023.
Jounral reviewer:
IEEE TPAMI, IEEE TIP, IEEE TMI, IEEE IV, Neurocomputing, Scientific Reports.
Teaching assistant:
CS 231n (Stanford, Spring 2024), CS 231n (Stanford, Spring 2023), COMP 3419 (USYD, Fall 2019)