8 citations · 24 across the 9 of their papers we have counts for
12 papers
Mask Guided Matting via Progressive Refinement Network
Qihang Yu, Jianming Zhang, He Zhang +5
We propose Mask Guided (MG) Matting, a robust matting framework that takes a general coarse mask as guidance. MG Matting leverages a network (PRN) design which encourages the matti…
Finding Action Tubes with a Sparse-to-Dense Framework
Yuxi Li, Weiyao Lin, Tao Wang +5
The task of spatial-temporal action detection has attracted increasing attention among researchers. Existing dominant methods solve this problem by relying on short-term informatio…
CFAD: Coarse-to-Fine Action Detector for Spatiotemporal Action Localization
Yuxi Li, Weiyao Lin, John See +4
Most current pipelines for spatio-temporal action localization connect frame-wise or clip-wise detection results to generate action proposals, where only local information is explo…
Video Question Answering on Screencast Tutorials
Wentian Zhao, Seokhwan Kim, Ning Xu +1
This paper presents a new video question answering task on screencast tutorials. We introduce a dataset including question, answer and context triples from the tutorial videos for…
Incorporating Reinforced Adversarial Learning in Autoregressive Image Generation
Kenan E. Ak, Ning Xu, Zhe Lin +1
Autoregressive models recently achieved comparable results versus state-of-the-art Generative Adversarial Networks (GANs) with the help of Vector Quantized Variational AutoEncoders…
Multiple Sound Sources Localization from Coarse to Fine
Rui Qian, Di Hu, Heinrich Dinkel +3
How to visually localize multiple sound sources in unconstrained videos is a formidable problem, especially when lack of the pairwise sound-object annotations. To solve this proble…