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DecideNet: Counting Varying Density Crowds Through Attention Guided Detection and Density Estimation
Jiang Liu, Chenqiang Gao, Deyu Meng +1
In real-world crowd counting applications, the crowd densities vary greatly in spatial and temporal domains. A detection based counting method will estimate crowds accurately in lo…
MemexQA: Visual Memex Question Answering
Lu Jiang, Junwei Liang, Liangliang Cao +3
This paper proposes a new task, MemexQA: given a collection of photos or videos from a user, the goal is to automatically answer questions that help users recover their memory abou…
Video Captioning with Guidance of Multimodal Latent Topics
Shizhe Chen, Jia Chen, Qin Jin +1
The topic diversity of open-domain videos leads to various vocabularies and linguistic expressions in describing video contents, and therefore, makes the video captioning task even…
Video Representation Learning and Latent Concept Mining for Large-scale Multi-label Video Classification
Po-Yao Huang, Ye Yuan, Zhenzhong Lan +2
We report on CMU Informedia Lab's system used in Google's YouTube 8 Million Video Understanding Challenge. In this multi-label video classification task, our pipeline achieved 84.6…
Hidden Two-Stream Convolutional Networks for Action Recognition
Yi Zhu, Zhenzhong Lan, Shawn Newsam +1
Analyzing videos of human actions involves understanding the temporal relationships among video frames. State-of-the-art action recognition approaches rely on traditional optical f…
Guided Optical Flow Learning
Yi Zhu, Zhenzhong Lan, Shawn Newsam +1
We study the unsupervised learning of CNNs for optical flow estimation using proxy ground truth data. Supervised CNNs, due to their immense learning capacity, have shown superior p…