30 citations · 66 across the 5 of their papers we have counts for
5 papers
Weakly-Supervised Action Localization with Expectation-Maximization Multi-Instance Learning
Zhekun Luo, Devin Guillory, Baifeng Shi +4
Weakly-supervised action localization requires training a model to localize the action segments in the video given only video level action label. It can be solved under the Multipl…
C-MIL: Continuation Multiple Instance Learning for Weakly Supervised Object Detection
Fang Wan, Chang Liu, Wei Ke +3
Weakly supervised object detection (WSOD) is a challenging task when provided with image category supervision but required to simultaneously learn object locations and object detec…
Linear Span Network for Object Skeleton Detection
Chang Liu, Wei Ke, Fei Qin +1
Robust object skeleton detection requires to explore rich representative visual features and effective feature fusion strategies. In this paper, we first re-visit the implementatio…
SRN: Side-output Residual Network for Object Symmetry Detection in the Wild
Wei Ke, Jie Chen, Jianbin Jiao +2
In this paper, we establish a baseline for object symmetry detection in complex backgrounds by presenting a new benchmark and an end-to-end deep learning approach, opening up a pro…
Self-learning Scene-specific Pedestrian Detectors using a Progressive Latent Model
Qixiang Ye, Tianliang Zhang, Qiang Qiu +3
In this paper, a self-learning approach is proposed towards solving scene-specific pedestrian detection problem without any human' annotation involved. The self-learning approach i…