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Victor Sanchez

23 papers hereh-index 201.7k citations111 works total

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

author position
  • middle author9
  • last author13

Across the 22 of 23 papers where every author was matched, so the position is known.

fields
  • cs.CV11
  • cs.MM7
  • cs.AI1
  • cs.DS1
  • cs.IR1
  • cs.OH1
same name
  • Victor Sanchez — 6 papers, h 3
  • Victor Sanchez — 5 papers, h 5
  • Victor Sanchez — 4 papers, h 2
  • Victor Sanchez — 4 papers, h 3
  • Victor Sanchez — 2 papers, h 2
  • Victor Sanchez — 2 papers, h 3

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
20162022
most citedImproving Face-Based Age Estimation with Attention-Based Dynamic Patch Fusion

56 citations · 224 across the 17 of their papers we have counts for

collaborators
Showing 2021Show all

4 papers · 1 filter

cs.CV2021★ 56 cited

Improving Face-Based Age Estimation with Attention-Based Dynamic Patch Fusion

Haoyi Wang, Victor Sanchez, Chang-Tsun Li

With the increasing popularity of convolutional neural networks (CNNs), recent works on face-based age estimation employ these networks as the backbone. However, state-of-the-art C…

cs.CV2021

Multi-Camera Trajectory Forecasting with Trajectory Tensors

Olly Styles, Tanaya Guha, Victor Sanchez

We introduce the problem of multi-camera trajectory forecasting (MCTF), which involves predicting the trajectory of a moving object across a network of cameras. While multi-camera…

cs.CV2021★ 44 cited

On the detection-to-track association for online multi-object tracking

Xufeng Lin, Chang-Tsun Li, Victor Sanchez +1

Driven by recent advances in object detection with deep neural networks, the tracking-by-detection paradigm has gained increasing prevalence in the research community of multi-obje…

cs.MM2021★ 14 cited

Deep Learning for Predictive Analytics in Reversible Steganography

Ching-Chun Chang, Xu Wang, Sisheng Chen +3

Deep learning is regarded as a promising solution for reversible steganography. There is an accelerating trend of representing a reversible steo-system by monolithic neural network…

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