Alapfogalmak
Color guidance plays a crucial role in depth map super-resolution, with the proposed hierarchical network achieving superior performance.
Kivonat
The content discusses the importance of color information in depth map super-resolution and introduces a hierarchical color guidance network. It explores the utilization of low-level and high-level color features to enhance detail restoration and maintain semantic consistency. The network architecture includes modules for low-level detail embedding, high-level abstract guidance, and attention-based feature projection. Experimental results demonstrate the effectiveness of the proposed method on various benchmark datasets.
Structure:
Introduction to Depth Maps and DSR Importance
Proposed Hierarchical Color Guidance Network Architecture
Detailed Explanation of Low-Level Detail Embedding Module
High-Level Abstract Guidance Module Design
Attention-Based Feature Projection Module Overview
Experimentation Details and Dataset Information
Performance Comparison with State-of-the-Art Methods
Statisztikák
著者らの方法は、4つのベンチマークデータセットで競争力のある性能を達成しています。
提案されたHCGNetは、他のSOTA手法よりも優れた全体的な平均MADパフォーマンスを実現しています。
Idézetek
"We rethink the utilization of color information in the DSR task and distinguish the roles of low-level and high-level color information."
"Our method achieves more competitive performance both qualitatively and quantitatively."