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Suryansh Kumar

Texas A&M University

32 papers hereh-index 211.2k citations52 works total

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

author position
  • sole author3
  • first author6
  • middle author17
  • last author6

Across the 32 of 32 papers where every author was matched, so the position is known.

fields
  • cs.CV32
affiliations
  • Texas A&M University
Homepage
same name
  • Suryansh Kumar — 3 papers
  • Suryansh Kumar — 2 papers, h 1

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
20172026
most citedTrilevel Neural Architecture Search for Efficient Single Image Super-Resolution

14 citations · 77 across the 21 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.CV2019

Superpixel Soup: Monocular Dense 3D Reconstruction of a Complex Dynamic Scene

Suryansh Kumar, Yuchao Dai, Hongdong Li

This work addresses the task of dense 3D reconstruction of a complex dynamic scene from images. The prevailing idea to solve this task is composed of a sequence of steps and is dep…

cs.CV2019★ 12 cited

Dense Depth Estimation of a Complex Dynamic Scene without Explicit 3D Motion Estimation

Suryansh Kumar, Ram Srivatsav Ghorakavi, Yuchao Dai +1

Recent geometric methods need reliable estimates of 3D motion parameters to procure accurate dense depth map of a complex dynamic scene from monocular images \cite{kumar2017monocul…

cs.CV2019

Non-Rigid Structure from Motion: Prior-Free Factorization Method Revisited

Suryansh Kumar

A simple prior free factorization algorithm \cite{dai2014simple} is quite often cited work in the field of Non-Rigid Structure from Motion (NRSfM). The benefit of this work lies in…

cs.CV2019

Jumping Manifolds: Geometry Aware Dense Non-Rigid Structure from Motion

Suryansh Kumar

Given dense image feature correspondences of a non-rigidly moving object across multiple frames, this paper proposes an algorithm to estimate its 3D shape for each frame. To solve…

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