25 citations · 66 across the 11 of their papers we have counts for
7 papers · 1 filter
Diverse Cotraining Makes Strong Semi-Supervised Segmentor
Yijiang Li, Xinjiang Wang, Lihe Yang +3
Deep co-training has been introduced to semi-supervised segmentation and achieves impressive results, yet few studies have explored the working mechanism behind it. In this work, w…
Group R-CNN for Weakly Semi-supervised Object Detection with Points
Shilong Zhang, Zhuoran Yu, Liyang Liu +3
We study the problem of weakly semi-supervised object detection with points (WSSOD-P), where the training data is combined by a small set of fully annotated images with bounding bo…
Temporal RoI Align for Video Object Recognition
Tao Gong, Kai Chen, Xinjiang Wang +5
Video object detection is challenging in the presence of appearance deterioration in certain video frames. Therefore, it is a natural choice to aggregate temporal information from…
Group Fisher Pruning for Practical Network Compression
Liyang Liu, Shilong Zhang, Zhanghui Kuang +7
Network compression has been widely studied since it is able to reduce the memory and computation cost during inference. However, previous methods seldom deal with complicated stru…
WSSOD: A New Pipeline for Weakly- and Semi-Supervised Object Detection
Shijie Fang, Yuhang Cao, Xinjiang Wang +3
The performance of object detection, to a great extent, depends on the availability of large annotated datasets. To alleviate the annotation cost, the research community has explor…
Scale-Equalizing Pyramid Convolution for Object Detection
Xinjiang Wang, Shilong Zhang, Zhuoran Yu +2
Feature pyramid has been an efficient method to extract features at different scales. Development over this method mainly focuses on aggregating contextual information at different…