109 citations · 144 across the 7 of their papers we have counts for
18 papers
Boosting Few-shot Semantic Segmentation with Transformers
Guolei Sun, Yun Liu, Jingyun Liang +1
Due to the fact that fully supervised semantic segmentation methods require sufficient fully-labeled data to work well and can not generalize to unseen classes, few-shot segmentati…
DOTS: Decoupling Operation and Topology in Differentiable Architecture Search
Yu-Chao Gu, Li-Juan Wang, Yun Liu +4
Differentiable Architecture Search (DARTS) has attracted extensive attention due to its efficiency in searching for cell structures. DARTS mainly focuses on the operation search an…
Generalized Zero-Shot Learning via VAE-Conditioned Generative Flow
Yu-Chao Gu, Le Zhang, Yun Liu +2
Generalized zero-shot learning (GZSL) aims to recognize both seen and unseen classes by transferring knowledge from semantic descriptions to visual representations. Recent generati…
Regularized Densely-connected Pyramid Network for Salient Instance Segmentation
Yu-Huan Wu, Yun Liu, Le Zhang +2
Much of the recent efforts on salient object detection (SOD) have been devoted to producing accurate saliency maps without being aware of their instance labels. To this end, we pro…
MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation
Shijie Li, Yazan Abu Farha, Yun Liu +2
With the success of deep learning in classifying short trimmed videos, more attention has been focused on temporally segmenting and classifying activities in long untrimmed videos.…
MiniSeg: An Extremely Minimum Network for Efficient COVID-19 Segmentation
Yu Qiu, Yun Liu, Shijie Li +1
The rapid spread of the new pandemic, i.e., COVID-19, has severely threatened global health. Deep-learning-based computer-aided screening, e.g., COVID-19 infected CT area segmentat…