16 citations · 49 across the 5 of their papers we have counts for
5 papers
Learning Implicit Feature Alignment Function for Semantic Segmentation
Hanzhe Hu, Yinbo Chen, Jiarui Xu +4
Integrating high-level context information with low-level details is of central importance in semantic segmentation. Towards this end, most existing segmentation models apply bilin…
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning
Hanzhe Hu, Fangyun Wei, Han Hu +3
Due to the limited and even imbalanced data, semi-supervised semantic segmentation tends to have poor performance on some certain categories, e.g., tailed categories in Cityscapes…
Dense Relation Distillation with Context-aware Aggregation for Few-Shot Object Detection
Hanzhe Hu, Shuai Bai, Aoxue Li +2
Conventional deep learning based methods for object detection require a large amount of bounding box annotations for training, which is expensive to obtain such high quality annota…
Context-Aware Graph Convolution Network for Target Re-identification
Deyi Ji, Haoran Wang, Hanzhe Hu +3
Most existing re-identification methods focus on learning robust and discriminative features with deep convolution networks. However, many of them consider content similarity separ…
Class-wise Dynamic Graph Convolution for Semantic Segmentation
Hanzhe Hu, Deyi Ji, Weihao Gan +3
Recent works have made great progress in semantic segmentation by exploiting contextual information in a local or global manner with dilated convolutions, pyramid pooling or self-a…