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Congyan Lang

10 papers hereh-index 242.8k citations157 works total

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

author position
  • middle author8
  • last author2

Across the 10 of 10 papers where every author was matched, so the position is known.

fields
  • cs.LG5
  • cs.CV4
  • eess.IV1
same name
  • Congyan Lang — 6 papers, h 2
  • Congyan Lang — 2 papers
  • Congyan Lang — 1 paper, h 5

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
20182024
most citedEDCNN: Edge enhancement-based Densely Connected Network with Compound Loss for Low-Dose CT Denoising

143 citations · 167 across the 9 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2022★ 1 cited

Deep Probabilistic Graph Matching

He Liu, Tao Wang, Yidong Li +3

Most previous learning-based graph matching algorithms solve the \textit{quadratic assignment problem} (QAP) by dropping one or more of the matching constraints and adopting a rela…

cs.CV2021★ 1 cited

MSO: Multi-Feature Space Joint Optimization Network for RGB-Infrared Person Re-Identification

Yajun Gao, Tengfei Liang, Yi Jin +4

The RGB-infrared cross-modality person re-identification (ReID) task aims to recognize the images of the same identity between the visible modality and the infrared modality. Exist…

cs.CV2021★ 1 cited

A Universal Model for Cross Modality Mapping by Relational Reasoning

Zun Li, Congyan Lang, Liqian Liang +4

With the aim of matching a pair of instances from two different modalities, cross modality mapping has attracted growing attention in the computer vision community. Existing method…

cs.CV2019★ 12 cited

Deep Reasoning with Multi-Scale Context for Salient Object Detection

Zun Li, Congyan Lang, Yunpeng Chen +2

To detect salient objects accurately, existing methods usually design complex backbone network architectures to learn and fuse powerful features. However, the saliency inference mo…

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