227 citations · 229 across the 3 of their papers we have counts for
8 papers · 1 filter
Delving into Transformer for Incremental Semantic Segmentation
Zekai Xu, Mingyi Zhang, Jiayue Hou +4
Incremental semantic segmentation(ISS) is an emerging task where old model is updated by incrementally adding new classes. At present, methods based on convolutional neural network…
MVP-Net: Multi-view FPN with Position-aware Attention for Deep Universal Lesion Detection
Zihao Li, Shu Zhang, Junge Zhang +3
Universal lesion detection (ULD) on computed tomography (CT) images is an important but underdeveloped problem. Recently, deep learning-based approaches have been proposed for ULD,…
SparseMask: Differentiable Connectivity Learning for Dense Image Prediction
Huikai Wu, Junge Zhang, Kaiqi Huang
In this paper, we aim at automatically searching an efficient network architecture for dense image prediction. Particularly, we follow the encoder-decoder style and focus on design…
FastFCN: Rethinking Dilated Convolution in the Backbone for Semantic Segmentation
Huikai Wu, Junge Zhang, Kaiqi Huang +2
Modern approaches for semantic segmentation usually employ dilated convolutions in the backbone to extract high-resolution feature maps, which brings heavy computation complexity a…
Transductive Zero-Shot Learning with Visual Structure Constraint
Ziyu Wan, Dongdong Chen, Yan Li +4
To recognize objects of the unseen classes, most existing Zero-Shot Learning(ZSL) methods first learn a compatible projection function between the common semantic space and the vis…
Discriminative Learning of Latent Features for Zero-Shot Recognition
Yan Li, Junge Zhang, Jianguo Zhang +1
Zero-shot learning (ZSL) aims to recognize unseen image categories by learning an embedding space between image and semantic representations. For years, among existing works, it ha…