Share Email Print
cover

Proceedings Paper • new

Modeling long range relations by feature translation
Author(s): Te Qi; Hongtao Lu; Huiyu Weng
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Long range relations play a key role in tasks like human pose estimation that requires dense prediction. We propose an additional module containing a process called feature translation, to gather long range information at early stages. It is shown that such module has connection with dilated convolution and is more efficient. The module significantly improves performance in pose estimation and we show that most of the improvement is contributed by the feature translation process.

Paper Details

Date Published: 15 March 2019
PDF: 7 pages
Proc. SPIE 11041, Eleventh International Conference on Machine Vision (ICMV 2018), 110412D (15 March 2019); doi: 10.1117/12.2522913
Show Author Affiliations
Te Qi, Shanghai Jiao Tong Univ. (China)
Hongtao Lu, Shanghai Jiao Tong Univ. (China)
Huiyu Weng, Shanghai Jiao Tong Univ. (China)


Published in SPIE Proceedings Vol. 11041:
Eleventh International Conference on Machine Vision (ICMV 2018)
Antanas Verikas; Dmitry P. Nikolaev; Petia Radeva; Jianhong Zhou, Editor(s)

© SPIE. Terms of Use
Back to Top