most citedHierarchical Video Generation from Orthogonal Information: Optical Flow and Texture

15 citations · 22 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV201715 cited

Hierarchical Video Generation from Orthogonal Information: Optical Flow and Texture

Katsunori Ohnishi, Shohei Yamamoto, Yoshitaka Ushiku +1

Learning to represent and generate videos from unlabeled data is a very challenging problem. To generate realistic videos, it is important not only to ensure that the appearance of…

cs.SD20177 cited

Melody Generation for Pop Music via Word Representation of Musical Properties

Andrew Shin, Leopold Crestel, Hiroharu Kato +6

Automatic melody generation for pop music has been a long-time aspiration for both AI researchers and musicians. However, learning to generate euphonious melody has turned out to b…

cs.CV2016

Beyond Caption To Narrative: Video Captioning With Multiple Sentences

Andrew Shin, Katsunori Ohnishi, Tatsuya Harada

Recent advances in image captioning task have led to increasing interests in video captioning task. However, most works on video captioning are focused on generating single input o…

cs.CV2016

Improved Dense Trajectory with Cross Streams

Katsunori Ohnishi, Masatoshi Hidaka, Tatsuya Harada

Improved dense trajectories (iDT) have shown great performance in action recognition, and their combination with the two-stream approach has achieved state-of-the-art performance.…

cs.CV2016

Dense Image Representation with Spatial Pyramid VLAD Coding of CNN for Locally Robust Captioning

Andrew Shin, Masataka Yamaguchi, Katsunori Ohnishi +1

The workflow of extracting features from images using convolutional neural networks (CNN) and generating captions with recurrent neural networks (RNN) has become a de-facto standar…