3 papers
cs.CV2026
WAVE: Reversing the Guidance Hierarchy for Coarse-to-Fine Guided Depth Super-Resolution
Tayyab Nasir, Daochang Liu, Ajmal Mian
Guided depth super-resolution (GDSR) typically extracts RGB guidance features through convolutional hierarchies, inheriting their fine-to-coarse bias. Thus, low-level spatial cues…
eess.IV2026
NAIMA: Semantics Aware RGB Guided Depth Super-Resolution
Tayyab Nasir, Daochang Liu, Ajmal Mian
Guided depth super-resolution (GDSR) is a multi-modal approach for depth map super-resolution that relies on a low-resolution depth map and a high-resolution RGB image to restore f…
cs.CV2026
Implicit Neural Representation-Based Continuous Single Image Super-Resolution: An Empirical Benchmark
Tayyab Nasir, Daochang Liu, Ajmal Mian
Implicit neural representation (INR) has become the standard approach for arbitrary-scale image super-resolution (ASSR). However, no systematic empirical study has examined the eff…