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Taimoor Tariq

5 papers hereh-index 483 citations11 works total

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

author position
  • first author2
  • middle author2

Across the 4 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.GR1

identity via Semantic Scholar / OpenAlex

activity
20182025
most citedTowards Understanding Depth Perception in Foveated Rendering

5 citations · 7 across the 4 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2025★ 5 cited

Towards Understanding Depth Perception in Foveated Rendering

Sophie Kergaßner, Taimoor Tariq, Piotr Didyk

The true vision for real-time virtual and augmented reality is reproducing our visual reality in its entirety on immersive displays. To this end, foveated rendering leverages the l…

cs.CV2024★ 1 cited

Human Vision Constrained Super-Resolution

Volodymyr Karpenko, Taimoor Tariq, Jorge Condor +1

Modern deep-learning super-resolution (SR) techniques process images and videos independently of the underlying content and viewing conditions. However, the sensitivity of the huma…

cs.CV2019★ 1 cited

A HVS-inspired Attention to Improve Loss Metrics for CNN-based Perception-Oriented Super-Resolution

Taimoor Tariq, Juan Luis Gonzalez, Munchurl Kim

Deep Convolutional Neural Network (CNN) features have been demonstrated to be effective perceptual quality features. The perceptual loss, based on feature maps of pre-trained CNN's…

cs.CV2018

Why Are Deep Representations Good Perceptual Quality Features?

Taimoor Tariq, Okan Tarhan Tursun, Munchurl Kim +1

Recently, intermediate feature maps of pre-trained convolutional neural networks have shown significant perceptual quality improvements, when they are used in the loss function for…

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