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Saeed Anwar

8 papers hereh-index 346 citations9 works total

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

author position
  • middle author8

Across the 8 of 8 papers where every author was matched, so the position is known.

fields
  • cs.CV7
  • eess.IV1
same name
  • Saeed Anwar — 45 papers, h 32
  • Saeed Anwar — 9 papers, h 5
  • Saeed Anwar — 7 papers, h 2
  • Saeed Anwar — 5 papers, h 4
  • Saeed Anwar — 2 papers, h 2
  • Saeed Anwar — 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
20212026
most citedDeep Learning Based 3D Segmentation: A Survey

44 citations · 44 across the 7 of their papers we have counts for

collaborators
Showing 2025Show all

4 papers · 1 filter

cs.CV2025

FLaTEC: Frequency-Disentangled Latent Triplanes for Efficient Compression of LiDAR Point Clouds

Xiaoge Zhang, Zijie Wu, Mingtao Feng +4

Point cloud compression methods jointly optimize bitrates and reconstruction distortion. However, balancing compression ratio and reconstruction quality is difficult because low-fr…

cs.CV2025

Multistream Network for LiDAR and Camera-based 3D Object Detection in Outdoor Scenes

Muhammad Ibrahim, Naveed Akhtar, Haitian Wang +2

Fusion of LiDAR and RGB data has the potential to enhance outdoor 3D object detection accuracy. To address real-world challenges in outdoor 3D object detection, fusion of LiDAR and…

cs.CV2025

PointDiffuse: A Dual-Conditional Diffusion Model for Enhanced Point Cloud Semantic Segmentation

Yong He, Hongshan Yu, Mingtao Feng +5

Diffusion probabilistic models are traditionally used to generate colors at fixed pixel positions in 2D images. Building on this, we extend diffusion models to point cloud semantic…

eess.IV2025

A Lightweight Model for Perceptual Image Compression via Implicit Priors

Hao Wei, Yanhui Zhou, Yiwen Jia +3

Perceptual image compression has shown strong potential for producing visually appealing results at low bitrates, surpassing classical standards and pixel-wise distortion-oriented…

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