406 citations · 3.1k across the 87 of their papers we have counts for
11 papers · 1 filter
Flow-Distilled IP Two-Stream Networks for Compressed Video Action Recognition
Shiyuan Huang, Xudong Lin, Svebor Karaman +1
Two-stream networks have achieved great success in video recognition. A two-stream network combines a spatial stream of RGB frames and a temporal stream of Optical Flow to make pre…
Learning to Learn Words from Visual Scenes
Dídac Surís, Dave Epstein, Heng Ji +2
Language acquisition is the process of learning words from the surrounding scene. We introduce a meta-learning framework that learns how to learn word representations from unconstr…
Towards Train-Test Consistency for Semi-supervised Temporal Action Localization
Xudong Lin, Zheng Shou, Shih-Fu Chang
Recently, Weakly-supervised Temporal Action Localization (WTAL) has been densely studied but there is still a large gap between weakly-supervised models and fully-supervised models…
Context-Gated Convolution
Xudong Lin, Lin Ma, Wei Liu +1
As the basic building block of Convolutional Neural Networks (CNNs), the convolutional layer is designed to extract local patterns and lacks the ability to model global context in…
Report of 2017 NSF Workshop on Multimedia Challenges, Opportunities and Research Roadmaps
Shih-Fu Chang, Alex Hauptmann, Louis-Philippe Morency +18
With the transformative technologies and the rapidly changing global R&D landscape, the multimedia and multimodal community is now faced with many new opportunities and uncertainti…
Variational Context: Exploiting Visual and Textual Context for Grounding Referring Expressions
Yulei Niu, Hanwang Zhang, Zhiwu Lu +1
We focus on grounding (i.e., localizing or linking) referring expressions in images, e.g., ``largest elephant standing behind baby elephant''. This is a general yet challenging vis…
Detecting and Simulating Artifacts in GAN Fake Images
Xu Zhang, Svebor Karaman, Shih-Fu Chang
To detect GAN generated images, conventional supervised machine learning algorithms require collection of a number of real and fake images from the targeted GAN model. However, the…
CDSA: Cross-Dimensional Self-Attention for Multivariate, Geo-tagged Time Series Imputation
Jiawei Ma, Zheng Shou, Alireza Zareian +3
Many real-world applications involve multivariate, geo-tagged time series data: at each location, multiple sensors record corresponding measurements. For example, air quality monit…
Unsupervised Embedding Learning via Invariant and Spreading Instance Feature
Mang Ye, Xu Zhang, Pong C. Yuen +1
This paper studies the unsupervised embedding learning problem, which requires an effective similarity measurement between samples in low-dimensional embedding space. Motivated by…
Unsupervised Rank-Preserving Hashing for Large-Scale Image Retrieval
Svebor Karaman, Xudong Lin, Xuefeng Hu +1
We propose an unsupervised hashing method which aims to produce binary codes that preserve the ranking induced by a real-valued representation. Such compact hash codes enable the c…
DMC-Net: Generating Discriminative Motion Cues for Fast Compressed Video Action Recognition
Zheng Shou, Xudong Lin, Yannis Kalantidis +4
Motion has shown to be useful for video understanding, where motion is typically represented by optical flow. However, computing flow from video frames is very time-consuming. Rece…