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Xin Wang

9 papers hereh-index 9530 citations16 works total

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

author position
  • middle author9

Across the 9 of 9 papers where every author was matched, so the position is known.

fields
  • cs.CV8
  • cs.RO1
same name
  • Xin Wang — 85 papers, h 39
  • Xin Wang — 56 papers, h 29
  • Xin Wang — 50 papers, h 28
  • Xin Wang — 35 papers, h 14
  • Xin Wang — 33 papers, h 5
  • Xin Wang — 31 papers, h 13

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
20182022
most citedBeyond Tracking: Selecting Memory and Refining Poses for Deep Visual Odometry

14 citations · 62 across the 9 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.CV2019★ 13 cited

Sequential Adversarial Learning for Self-Supervised Deep Visual Odometry

Shunkai Li, Fei Xue, Xin Wang +2

We propose a self-supervised learning framework for visual odometry (VO) that incorporates correlation of consecutive frames and takes advantage of adversarial learning. Previous m…

cs.CV2019★ 10 cited

Local Supports Global: Deep Camera Relocalization with Sequence Enhancement

Fei Xue, Xin Wang, Zike Yan +3

We propose to leverage the local information in image sequences to support global camera relocalization. In contrast to previous methods that regress global poses from single image…

cs.CV2019★ 13 cited

ACE: Adapting to Changing Environments for Semantic Segmentation

Zuxuan Wu, Xin Wang, Joseph E. Gonzalez +2

Deep neural networks exhibit exceptional accuracy when they are trained and tested on the same data distributions. However, neural classifiers are often extremely brittle when conf…

cs.CV2019★ 14 cited

Beyond Tracking: Selecting Memory and Refining Poses for Deep Visual Odometry

Fei Xue, Xin Wang, Shunkai Li +3

Most previous learning-based visual odometry (VO) methods take VO as a pure tracking problem. In contrast, we present a VO framework by incorporating two additional components call…

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