Self-Supervised Perceptually Interpretable Monocular Depth Estimation

arXiv:2609.30987 · cs.CV · Submitted 2026-09-25 · Read on arXiv

cs.CV

Submitted: 2026-09-25

Updated: 2026-09-25

Comments: Published at IEEE ICIP 2026; 6 pages, 4 figures

Journal ref: 2026 IEEE International Conference on Image Processing (ICIP), pp. 1-6, 2026

DOI: 10.1109/ICIP61757.2026.11630094

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Interpretability — 10× in this paper · explained in 15 episodes
• Accuracy — 3× in this paper · explained in 1 episode
• Benchmark — 3× in this paper · explained in 2 episodes
• Consistency — 3× in this paper · explained in 3 episodes
• Conference on Computer Vision and Pattern Recognition — 2× in this paper
• Transformer — 2× in this paper · explained in 2 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Core — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• International Conference on Computer Vision — 1× in this paper
• Latent Space — 1× in this paper · explained in 7 episodes
• Perceptual Alignment — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Root Mean Squared Error — 1× in this paper
• Transformer Architecture — 1× in this paper · explained in 2 episodes
• Wavelet Transform — 1× in this paper · explained in 2 episodes

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