Title
Watch, Reason and Code: Learning to Represent Videos Using Program
Abstract
Humans have a surprising capacity to induce general rules that describe the specific actions portrayed in a video sequence. The rules learned through this kind of process allow us to achieve similar goals to those shown in the video but in more general circumstances. Enabling an agent to achieve the same capacity represents a significant challenge. In this paper, we propose a Watch-Reason-Code(WRC) model to synthesise programs that describe the process carried out in a set of video sequences. The 'watch' stage is simply a video encoder that encodes videos to multiple feature vectors. The 'reason' stage takes as input the features from multiple diverse videos and generates a compact feature representation via a novel deviation-pooling method. The 'code' stage is a multi-sound decoder that the first step leverages to generate a draft program layout with possible useful statements and perceptions. Further steps then take these outputs and generate a fully structured, compile-able and executable program. We evaluate the effectiveness of our model in two video-to-program synthesis environments, Karel andVizDoom, showing that we can achieve the state-of-the-art under a variety of settings.
Year
DOI
Venue
2019
10.1145/3343031.3351094
Proceedings of the 27th ACM International Conference on Multimedia
Keywords
Field
DocType
video embedding, video to program translation, video understanding
Computer science,Multimedia
Conference
ISBN
Citations 
PageRank 
978-1-4503-6889-6
0
0.34
References 
Authors
0
7
Name
Order
Citations
PageRank
Xuguang Duan142.07
Qi Wu239641.54
Chuang Gan325331.92
Yiwei Zhang45212.65
Wen-bing Huang516718.91
Anton van den Hengel63710174.30
Wenwu Zhu74399300.42