415 citations · 770 across the 14 of their papers we have counts for
5 papers · 1 filter
GINet: Graph Interaction Network for Scene Parsing
Tianyi Wu, Yu Lu, Yu Zhu +4
Recently, context reasoning using image regions beyond local convolution has shown great potential for scene parsing. In this work, we explore how to incorporate the linguistic kno…
FGSD: A Dataset for Fine-Grained Ship Detection in High Resolution Satellite Images
Kaiyan Chen, Ming Wu, Jiaming Liu +1
Ship detection using high-resolution remote sensing images is an important task, which contribute to sea surface regulation. The complex background and special visual angle make sh…
Weakly Supervised Attention Pyramid Convolutional Neural Network for Fine-Grained Visual Classification
Yifeng Ding, Shaoguo Wen, Jiyang Xie +4
Classifying the sub-categories of an object from the same super-category (e.g. bird species, car and aircraft models) in fine-grained visual classification (FGVC) highly relies on…
The Devil is in the Channels: Mutual-Channel Loss for Fine-Grained Image Classification
Dongliang Chang, Yifeng Ding, Jiyang Xie +6
Key for solving fine-grained image categorization is finding discriminate and local regions that correspond to subtle visual traits. Great strides have been made, with complex netw…
C-DLinkNet: considering multi-level semantic features for human parsing
Yu Lu, Muyan Feng, Ming Wu +1
Human parsing is an essential branch of semantic segmentation, which is a fine-grained semantic segmentation task to identify the constituent parts of human. The challenge of human…