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Tyng-Luh Liu

21 papers hereh-index 345.3k citations110 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author1
  • middle author4
  • last author15

Across the 20 of 21 papers where every author was matched, so the position is known.

fields
  • cs.CV17
  • eess.IV2
  • cs.LG1
  • cs.SI1
same name
  • Tyng-Luh Liu — 1 paper
  • Tyng-Luh Liu — 1 paper, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20142026
most citedOne-Shot Object Detection with Co-Attention and Co-Excitation

116 citations · 301 across the 21 of their papers we have counts for

collaborators
Showing 2018Show all

4 papers · 1 filter

cs.CV2018

Unsupervised Meta-learning of Figure-Ground Segmentation via Imitating Visual Effects

Ding-Jie Chen, Jui-Ting Chien, Hwann-Tzong Chen +1

This paper presents a "learning to learn" approach to figure-ground image segmentation. By exploring webly-abundant images of specific visual effects, our method can effectively le…

cs.CV2018

Non-local RoI for Cross-Object Perception

Shou-Yao Roy Tseng, Hwann-Tzong Chen, Shao-Heng Tai +1

We present a generic and flexible module that encodes region proposals by both their intrinsic features and the extrinsic correlations to the others. The proposed non-local region…

cs.CV2018

Non-local RoIs for Instance Segmentation

Shou-Yao Roy Tseng, Hwann-Tzong Chen, Shao-Heng Tai +1

We introduce the concept of Non-Local RoI (NL-RoI) Block as a generic and flexible module that can be seamlessly adapted into different Mask R-CNN heads for various tasks. Mask R-C…

cs.CV2018★ 3 cited

Cube Padding for Weakly-Supervised Saliency Prediction in 360° Videos

Hsien-Tzu Cheng, Chun-Hung Chao, Jin-Dong Dong +3

Automatic saliency prediction in 360° videos is critical for viewpoint guidance applications (e.g., Facebook 360 Guide). We propose a spatial-temporal network which is (1) weakly-s…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.