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Xiaojie Jin

45 papers hereh-index 305.2k citations64 works total

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

author position
  • first author8
  • middle author29
  • last author8

Across the 45 of 45 papers where every author was matched, so the position is known.

fields
  • cs.CV43
  • cs.LG2
same name
  • Xiaojie Jin — 10 papers, h 3
  • Xiaojie Jin — 4 papers, h 2
  • Xiaojie Jin — 3 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
20152025
most citedDeepViT: Towards Deeper Vision Transformer

349 citations · 1.3k across the 44 of their papers we have counts for

collaborators
Showing 2016Show all

4 papers · 1 filter

cs.CV2016★ 6 cited

Video Scene Parsing with Predictive Feature Learning

Xiaojie Jin, Xin Li, Huaxin Xiao +9

In this work, we address the challenging video scene parsing problem by developing effective representation learning methods given limited parsing annotations. In particular, we co…

cs.CV2016★ 13 cited

Multi-Path Feedback Recurrent Neural Network for Scene Parsing

Xiaojie Jin, Yunpeng Chen, Jiashi Feng +2

In this paper, we consider the scene parsing problem and propose a novel Multi-Path Feedback recurrent neural network (MPF-RNN) for parsing scene images. MPF-RNN can enhance the ca…

cs.CV2016★ 4 cited

Collaborative Layer-wise Discriminative Learning in Deep Neural Networks

Xiaojie Jin, Yunpeng Chen, Jian Dong +2

Intermediate features at different layers of a deep neural network are known to be discriminative for visual patterns of different complexities. However, most existing works ignore…

cs.CV2016★ 61 cited

Training Skinny Deep Neural Networks with Iterative Hard Thresholding Methods

Xiaojie Jin, Xiaotong Yuan, Jiashi Feng +1

Deep neural networks have achieved remarkable success in a wide range of practical problems. However, due to the inherent large parameter space, deep models are notoriously prone t…

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