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researcher

Andrew I. Comport

3 papers here

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

author position
  • middle author2
  • last author1

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.CV3
ORCID 0000-0002-3959-3195

identity via Semantic Scholar / OpenAlex

most citedSTDepthFormer: Predicting Spatio-temporal Depth from Video with a Self-supervised Transformer Model

2 citations · 2 across the 3 of their papers we have counts for

collaborators

3 papers

cs.CV2024

HFGaussian: Learning Generalizable Gaussian Human with Integrated Human Features

Arnab Dey, Cheng-You Lu, Andrew I. Comport +3

Recent advancements in radiance field rendering show promising results in 3D scene representation, where Gaussian splatting-based techniques emerge as state-of-the-art due to their…

cs.CV2024

GHNeRF: Learning Generalizable Human Features with Efficient Neural Radiance Fields

Arnab Dey, Di Yang, Rohith Agaram +4

Recent advances in Neural Radiance Fields (NeRF) have demonstrated promising results in 3D scene representations, including 3D human representations. However, these representations…

cs.CV2023★ 2 cited

STDepthFormer: Predicting Spatio-temporal Depth from Video with a Self-supervised Transformer Model

Houssem Boulahbal, Adrian Voicila, Andrew Comport

In this paper, a self-supervised model that simultaneously predicts a sequence of future frames from video-input with a novel spatial-temporal attention (ST) network is proposed. T…

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