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researcher

W. Feng

5 papers hereh-index 191.4k citations133 works total

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

author position
  • middle author3
  • last author2

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.CR1
same name
  • W. Feng — 35 papers, h 30
  • W. Feng — 29 papers, h 38
  • W. Feng — 12 papers, h 5
  • W. Feng — 10 papers, h 13
  • W. Feng — 10 papers, h 14
  • W. Feng — 4 papers, h 2

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
20202023
most citedMM-FSOD: Meta and metric integrated few-shot object detection

8 citations · 10 across the 5 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2023

Iterative Robust Visual Grounding with Masked Reference based Centerpoint Supervision

Menghao Li, Chunlei Wang, Wenquan Feng +5

Visual Grounding (VG) aims at localizing target objects from an image based on given expressions and has made significant progress with the development of detection and vision tran…

cs.CV2022

Look in Different Views: Multi-Scheme Regression Guided Cell Instance Segmentation

Menghao Li, Wenquan Feng, Shuchang Lyu +2

Cell instance segmentation is a new and challenging task aiming at joint detection and segmentation of every cell in an image. Recently, many instance segmentation methods have app…

cs.CV2021★ 2 cited

PGGANet: Pose Guided Graph Attention Network for Person Re-identification

Zhijun He, Hongbo Zhao, Wenquan Feng

Person re-identification (reID) aims at retrieving a person from images captured by different cameras. For deep-learning-based reID methods, it has been proved that using local fea…

cs.CV2020★ 8 cited

MM-FSOD: Meta and metric integrated few-shot object detection

Yuewen Li, Wenquan Feng, Shuchang Lyu +2

In the object detection task, CNN (Convolutional neural networks) models always need a large amount of annotated examples in the training process. To reduce the dependency of expen…

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