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researcher

Yi Feng

13 papers hereh-index 9221 citations17 works total

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

author position
  • first author5
  • middle author7

Across the 12 of 13 papers where every author was matched, so the position is known.

fields
  • cs.CV11
  • cs.RO2
same name
  • Yi Feng — 51 papers, h 16
  • Yi Feng — 7 papers, h 8
  • Yi Feng — 6 papers, h 4
  • Yi Feng — 6 papers, h 4
  • Yi Feng — 6 papers, h 3
  • Yi Feng — 5 papers, h 6

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
20232026
most citedS3M-Net: Joint Learning of Semantic Segmentation and Stereo Matching for Autonomous Driving

36 citations · 47 across the 11 of their papers we have counts for

collaborators
Showing 2023Show all

4 papers · 1 filter

cs.RO2023

Three-Filters-to-Normal+: Revisiting Discontinuity Discrimination in Depth-to-Normal Translation

Jingwei Yang, Bohuan Xue, Yi Feng +3

This article introduces three-filters-to-normal+ (3F2N+), an extension of our previous work three-filters-to-normal (3F2N), with a specific focus on incorporating discontinuity dis…

cs.RO2023★ 9 cited

Freespace Optical Flow Modeling for Automated Driving

Yi Feng, Ruge Zhang, Jiayuan Du +2

Optical flow and disparity are two informative visual features for autonomous driving perception. They have been used for a variety of applications, such as obstacle and lane detec…

cs.CV2023★ 1 cited

D2NT: A High-Performing Depth-to-Normal Translator

Yi Feng, Bohuan Xue, Ming Liu +2

Surface normal holds significant importance in visual environmental perception, serving as a source of rich geometric information. However, the state-of-the-art (SoTA) surface norm…

cs.CV2023★ 1 cited

UDTIRI: An Online Open-Source Intelligent Road Inspection Benchmark Suite

Sicen Guo, Jiahang Li, Yi Feng +7

In the nascent domain of urban digital twins (UDT), the prospects for leveraging cutting-edge deep learning techniques are vast and compelling. Particularly within the specialized…

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