39 citations · 134 across the 9 of their papers we have counts for
9 papers
M-VOS: Multi-Phase, Multi-Transition, and Multi-Scenery Video Object Segmentation
Zixuan Chen, Jiaxin Li, Liming Tan +4
Intelligent robots need to interact with diverse objects across various environments. The appearance and state of objects frequently undergo complex transformations depending on th…
Detailed 2D-3D Joint Representation for Human-Object Interaction
Yong-Lu Li, Xinpeng Liu, Han Lu +4
Human-Object Interaction (HOI) detection lies at the core of action understanding. Besides 2D information such as human/object appearance and locations, 3D pose is also usually uti…
PaStaNet: Toward Human Activity Knowledge Engine
Yong-Lu Li, Liang Xu, Xinpeng Liu +7
Existing image-based activity understanding methods mainly adopt direct mapping, i.e. from image to activity concepts, which may encounter performance bottleneck since the huge gap…
Symmetry and Group in Attribute-Object Compositions
Yong-Lu Li, Yue Xu, Xiaohan Mao +1
Attributes and objects can compose diverse compositions. To model the compositional nature of these general concepts, it is a good choice to learn them through transformations, suc…
InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting
Hao-Shu Fang, Jianhua Sun, Runzhong Wang +3
Instance segmentation requires a large number of training samples to achieve satisfactory performance and benefits from proper data augmentation. To enlarge the training set and in…
HAKE: Human Activity Knowledge Engine
Yong-Lu Li, Liang Xu, Xinpeng Liu +7
Human activity understanding is crucial for building automatic intelligent system. With the help of deep learning, activity understanding has made huge progress recently. But some…
Transferable Interactiveness Knowledge for Human-Object Interaction Detection
Yong-Lu Li, Siyuan Zhou, Xijie Huang +5
Human-Object Interaction (HOI) Detection is an important problem to understand how humans interact with objects. In this paper, we explore Interactiveness Knowledge which indicates…
SRDA: Generating Instance Segmentation Annotation Via Scanning, Reasoning And Domain Adaptation
Wenqiang Xu, Yonglu Li, Cewu Lu
Instance segmentation is a problem of significance in computer vision. However, preparing annotated data for this task is extremely time-consuming and costly. By combining the adva…
Beyond Holistic Object Recognition: Enriching Image Understanding with Part States
Cewu Lu, Hao Su, Yongyi Lu +3
Important high-level vision tasks such as human-object interaction, image captioning and robotic manipulation require rich semantic descriptions of objects at part level. Based upo…