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Jie Shen

19 papers hereh-index 201.8k citations46 works total

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

author position
  • middle author19

Across the 19 of 19 papers where every author was matched, so the position is known.

fields
  • cs.CV15
  • cs.GR1
  • cs.HC1
  • cs.RO1
  • cs.SD1
same name
  • Jie Shen — 31 papers, h 5
  • Jie Shen — 28 papers, h 19
  • Jie Shen — 25 papers, h 45
  • Jie Shen — 19 papers, h 83
  • Jie Shen — 14 papers, h 12
  • Jie Shen — 7 papers, h 1

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
20182026
most citedSEWA DB: A Rich Database for Audio-Visual Emotion and Sentiment Research in the Wild

244 citations · 510 across the 18 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.CV2019★ 1 cited

Towards Pose-invariant Lip-Reading

Shiyang Cheng, Pingchuan Ma, Georgios Tzimiropoulos +4

Lip-reading models have been significantly improved recently thanks to powerful deep learning architectures. However, most works focused on frontal or near frontal views of the mou…

cs.CV2019

Shape Constrained Network for Eye Segmentation in the Wild

Bingnan Luo, Jie Shen, Shiyang Cheng +2

Semantic segmentation of eyes has long been a vital pre-processing step in many biometric applications. Majority of the works focus only on high resolution eye images, while little…

cs.CV2019★ 18 cited

Dynamic Face Video Segmentation via Reinforcement Learning

Yujiang Wang, Mingzhi Dong, Jie Shen +3

For real-time semantic video segmentation, most recent works utilised a dynamic framework with a key scheduler to make online key/non-key decisions. Some works used a fixed key sch…

cs.HC2019★ 244 cited

SEWA DB: A Rich Database for Audio-Visual Emotion and Sentiment Research in the Wild

Jean Kossaifi, Robert Walecki, Yannis Panagakis +10

Natural human-computer interaction and audio-visual human behaviour sensing systems, which would achieve robust performance in-the-wild are more needed than ever as digital devices…

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