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Shengjin Wang

56 papers hereh-index 5019.3k citations254 works total

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

author position
  • middle author17
  • last author37

Across the 54 of 56 papers where every author was matched, so the position is known.

fields
  • cs.CV51
  • cs.RO2
  • cs.IR1
  • eess.IV1
  • physics.optics1
same name
  • Shengjin Wang — 6 papers, h 7
  • Shengjin Wang — 1 paper
  • Shengjin Wang — 1 paper, h 2
  • Shengjin Wang — 1 paper, h 0
  • Shengjin Wang — 1 paper, h 5
  • Shengjin Wang — 1 paper, 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
20142023
most citedBeyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)

152 citations · 1.1k across the 56 of their papers we have counts for

collaborators
Showing 2020Show all

4 papers · 1 filter

eess.IV2020★ 63 cited

Revisiting Temporal Modeling for Video Super-resolution

Takashi Isobe, Fang Zhu, Xu Jia +1

Video super-resolution plays an important role in surveillance video analysis and ultra-high-definition video display, which has drawn much attention in both the research and indus…

cs.CV2020★ 15 cited

Video Super-Resolution with Recurrent Structure-Detail Network

Takashi Isobe, Xu Jia, Shuhang Gu +3

Most video super-resolution methods super-resolve a single reference frame with the help of neighboring frames in a temporal sliding window. They are less efficient compared to the…

cs.CV2020★ 9 cited

Video Super-resolution with Temporal Group Attention

Takashi Isobe, Songjiang Li, Xu Jia +6

Video super-resolution, which aims at producing a high-resolution video from its corresponding low-resolution version, has recently drawn increasing attention. In this work, we pro…

cs.CV2020★ 13 cited

CycAs: Self-supervised Cycle Association for Learning Re-identifiable Descriptions

Zhongdao Wang, Jingwei Zhang, Liang Zheng +4

This paper proposes a self-supervised learning method for the person re-identification (re-ID) problem, where existing unsupervised methods usually rely on pseudo labels, such as t…

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