23 citations · 67 across the 13 of their papers we have counts for
7 papers · 1 filter
3D Medical Point Transformer: Introducing Convolution to Attention Networks for Medical Point Cloud Analysis
Jianhui Yu, Chaoyi Zhang, Heng Wang +5
General point clouds have been increasingly investigated for different tasks, and recently Transformer-based networks are proposed for point cloud analysis. However, there are bare…
SQUID: Deep Feature In-Painting for Unsupervised Anomaly Detection
Tiange Xiang, Yixiao Zhang, Yongyi Lu +4
Radiography imaging protocols focus on particular body regions, therefore producing images of great similarity and yielding recurrent anatomical structures across patients. To expl…
DSNet: A Dual-Stream Framework for Weakly-Supervised Gigapixel Pathology Image Analysis
Tiange Xiang, Yang Song, Chaoyi Zhang +6
We present a novel weakly-supervised framework for classifying whole slide images (WSIs). WSIs, due to their gigapixel resolution, are commonly processed by patch-wise classificati…
BiX-NAS: Searching Efficient Bi-directional Architecture for Medical Image Segmentation
Xinyi Wang, Tiange Xiang, Chaoyi Zhang +4
The recurrent mechanism has recently been introduced into U-Net in various medical image segmentation tasks. Existing studies have focused on promoting network recursion via reusin…
Partial Graph Reasoning for Neural Network Regularization
Tiange Xiang, Chaoyi Zhang, Yang Song +3
Regularizers help deep neural networks prevent feature co-adaptations. Dropout, as a commonly used regularization technique, stochastically disables neuron activations during netwo…
Walk in the Cloud: Learning Curves for Point Clouds Shape Analysis
Tiange Xiang, Chaoyi Zhang, Yang Song +2
Discrete point cloud objects lack sufficient shape descriptors of 3D geometries. In this paper, we present a novel method for aggregating hypothetical curves in point clouds. Seque…
Two-Stage Monte Carlo Denoising with Adaptive Sampling and Kernel Pool
Tiange Xiang, Hongliang Yuan, Haozhi Huang +1
Monte Carlo path tracer renders noisy image sequences at low sampling counts. Although great progress has been made on denoising such sequences, existing methods still suffer from…