WAVE: Reversing the Guidance Hierarchy for Coarse-to-Fine Guided Depth Super-Resolution

arXiv:2608.25302 · cs.CV, cs.LG · Submitted 2026-08-26 · Read on arXiv

cs.CV, cs.LG

Submitted: 2026-08-26

Updated: 2026-08-26

Code: https://github.com/tayyabnasir22/WAVE

Terminology

• Benchmark — 8× in this paper · explained in 2 episodes
• Ablation — 7× in this paper · explained in 1 episode
• Foundation Model — 6× in this paper · explained in 3 episodes
• Transformer — 6× in this paper · explained in 2 episodes
• Abstraction — 4× in this paper · explained in 1 episode
• Robustness — 4× in this paper · explained in 5 episodes
• Wavelet Transform — 4× in this paper · explained in 2 episodes
• Adaptation — 3× in this paper · explained in 1 episode
• Foundation Models — 3× in this paper · explained in 7 episodes
• Benchmarking — 2× in this paper · explained in 3 episodes
• Distillation — 2× in this paper · explained in 2 episodes
• Feature Extraction — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Knowledge Distillation — 2× in this paper · explained in 11 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Convolutional Neural Networks (CNNs) — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Hierarchical Upsampling with Multi-band Multiresolution Approximation — 1× in this paper
• Latent Space — 1× in this paper · explained in 7 episodes
• Matrix Completion — 1× in this paper · explained in 4 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes

Sources

• DIML/CVL RGB-D Dataset: 2M RGB-D Images of Natural Indoor and Outdoor Scenes
• Depth Anything 3: Recovering the Visual Space from Any Views
• Implicit Neural Representation-Based Continuous Single Image Super-Resolution: An Empirical Benchmark
• NAIMA: Semantics Aware RGB Guided Depth Super-Resolution
• DINOv2: Learning Robust Visual Features without Supervision
• DINOv3
• Scene Prior Filtering for Depth Super-Resolution

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