5 citations · 6 across the 5 of their papers we have counts for
6 papers
Learning to Generate Scene Graph from Natural Language Supervision
Yiwu Zhong, Jing Shi, Jianwei Yang +2
Learning from image-text data has demonstrated recent success for many recognition tasks, yet is currently limited to visual features or individual visual concepts such as objects.…
Learning by Planning: Language-Guided Global Image Editing
Jing Shi, Ning Xu, Yihang Xu +3
Recently, language-guided global image editing draws increasing attention with growing application potentials. However, previous GAN-based methods are not only confined to domain-s…
A Benchmark and Baseline for Language-Driven Image Editing
Jing Shi, Ning Xu, Trung Bui +3
Language-driven image editing can significantly save the laborious image editing work and be friendly to the photography novice. However, most similar work can only deal with a spe…
Cubic Spline Smoothing Compensation for Irregularly Sampled Sequences
Jing Shi, Jing Bi, Yingru Liu +1
The marriage of recurrent neural networks and neural ordinary differential networks (ODE-RNN) is effective in modeling irregularly-observed sequences. While ODE produces the smooth…
Actor-Action Video Classification CSC 249/449 Spring 2020 Challenge Report
Jing Shi, Zhiheng Li, Haitian Zheng +30
This technical report summarizes submissions and compiles from Actor-Action video classification challenge held as a final project in CSC 249/449 Machine Vision course (Spring 2020…
GAN-EM: GAN based EM learning framework
Wentian Zhao, Shaojie Wang, Zhihuai Xie +2
Expectation maximization (EM) algorithm is to find maximum likelihood solution for models having latent variables. A typical example is Gaussian Mixture Model (GMM) which requires…