56 citations · 73 across the 5 of their papers we have counts for
5 papers
Depth-Guided Sparse Structure-from-Motion for Movies and TV Shows
Sheng Liu, Xiaohan Nie, Raffay Hamid
Existing approaches for Structure from Motion (SfM) produce impressive 3-D reconstruction results especially when using imagery captured with large parallax. However, to create eng…
Movies2Scenes: Using Movie Metadata to Learn Scene Representation
Shixing Chen, Chun-Hao Liu, Xiang Hao +3
Understanding scenes in movies is crucial for a variety of applications such as video moderation, search, and recommendation. However, labeling individual scenes is a time-consumin…
Shot Contrastive Self-Supervised Learning for Scene Boundary Detection
Shixing Chen, Xiaohan Nie, David Fan +3
Scenes play a crucial role in breaking the storyline of movies and TV episodes into semantically cohesive parts. However, given their complex temporal structure, finding scene boun…
Attribute And-Or Grammar for Joint Parsing of Human Attributes, Part and Pose
Seyoung Park, Bruce Xiaohan Nie, Song-Chun Zhu
This paper presents an attribute and-or grammar (A-AOG) model for jointly inferring human body pose and human attributes in a parse graph with attributes augmented to nodes in the…
Cross-view Action Modeling, Learning and Recognition
Jiang wang, Xiaohan Nie, Yin Xia +2
Existing methods on video-based action recognition are generally view-dependent, i.e., performing recognition from the same views seen in the training data. We present a novel mult…