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researcher

Qi Bi

5 papers hereh-index 201.8k citations28 works total

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

author position
  • first author2
  • middle author2

Across the 4 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CV3
  • eess.IV2
same name
  • Qi Bi — 6 papers, h 9
  • Qi Bi — 5 papers, h 2
  • Qi Bi — 4 papers, h 3
  • Qi Bi — 4 papers, h 2
  • Qi Bi — 2 papers, h 2
  • Qi Bi — 1 paper, 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
20192023
most citedPromoting Saliency From Depth: Deep Unsupervised RGB-D Saliency Detection

16 citations · 16 across the 2 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2023

Learning Content-enhanced Mask Transformer for Domain Generalized Urban-Scene Segmentation

Qi Bi, Shaodi You, Theo Gevers

Domain-generalized urban-scene semantic segmentation (USSS) aims to learn generalized semantic predictions across diverse urban-scene styles. Unlike domain gap challenges, USSS is…

cs.CV2023

Segment Anything Is Not Always Perfect: An Investigation of SAM on Different Real-world Applications

Wei Ji, Jingjing Li, Qi Bi +3

Recently, Meta AI Research approaches a general, promptable Segment Anything Model (SAM) pre-trained on an unprecedentedly large segmentation dataset (SA-1B). Without a doubt, the…

cs.CV2022★ 16 cited

Promoting Saliency From Depth: Deep Unsupervised RGB-D Saliency Detection

Wei Ji, Jingjing Li, Qi Bi +3

Growing interests in RGB-D salient object detection (RGB-D SOD) have been witnessed in recent years, owing partly to the popularity of depth sensors and the rapid progress of deep…

cs.CV2019

Multiple instance dense connected convolution neural network for aerial image scene classification

Qi Bi, Kun Qin, Zhili Li +2

With the development of deep learning, many state-of-the-art natural image scene classification methods have demonstrated impressive performance. While the current convolution neur…

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