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researcher

X. Wang

56 papers hereh-index 4522.8k citations236 works total

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

author position
  • first author15
  • middle author26
  • last author15

Across the 56 of 56 papers where every author was matched, so the position is known.

fields
  • cs.CV45
  • cs.AI2
  • cs.LG2
  • cs.CL1
  • cs.DC1
  • cs.GT1
same name
  • X. Wang — 422 papers, h 49
  • X. Wang — 183 papers, h 43
  • X. Wang — 167 papers, h 3
  • X. Wang — 154 papers, h 75
  • X. Wang — 151 papers
  • X. Wang — 125 papers, h 17

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
20142026
most citedUnsupervised Learning of Visual Representations using Videos

195 citations · 1.4k across the 56 of their papers we have counts for

collaborators
Showing 2017Show all

4 papers · 1 filter

cs.CV2017★ 150 cited

Non-local Neural Networks

Xiaolong Wang, Ross Girshick, Abhinav Gupta +1

Both convolutional and recurrent operations are building blocks that process one local neighborhood at a time. In this paper, we present non-local operations as a generic family of…

cs.CV2017★ 22 cited

Transitive Invariance for Self-supervised Visual Representation Learning

Xiaolong Wang, Kaiming He, Abhinav Gupta

Learning visual representations with self-supervised learning has become popular in computer vision. The idea is to design auxiliary tasks where labels are free to obtain. Most of…

cs.CV2017★ 13 cited

Temporal Dynamic Graph LSTM for Action-driven Video Object Detection

Yuan Yuan, Xiaodan Liang, Xiaolong Wang +2

In this paper, we investigate a weakly-supervised object detection framework. Most existing frameworks focus on using static images to learn object detectors. However, these detect…

cs.CV2017★ 7 cited

A-Fast-RCNN: Hard Positive Generation via Adversary for Object Detection

Xiaolong Wang, Abhinav Shrivastava, Abhinav Gupta

How do we learn an object detector that is invariant to occlusions and deformations? Our current solution is to use a data-driven strategy -- collect large-scale datasets which hav…

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