WebOct 30, 2024 · Depth completion deals with the problem of recovering dense depth maps from sparse ones, where color images are often used to facilitate this task. Recent approaches mainly focus on image guided learning frameworks to predict dense depth. ... CSPN studies the affinity matrix to refine coarse depth maps with spatial propagation … WebOct 19, 2024 · GraphCSPN: Geometry-Aware Depth Completion via Dynamic GCNs. Image guided depth completion aims to recover per-pixel dense depth maps from sparse depth measurements with the help of aligned color images, which has a wide range of applications from robotics to autonomous driving. However, the 3D nature of sparse-to …
Sensors Free Full-Text SGSNet: A Lightweight Depth Completion ...
WebDec 2, 2024 · CSPN is applied to depth completion, with the affinity matrix predicted by the RGB image used to propagate sparse depth values. Cheng et al. [ cspn++ ] further … WebAug 1, 2024 · Depth estimation from a single image is a fundamental problem in computer vision.In this paper, we propose a simple yet effective convolutional spatial propagation network (CSPN) to learn the affinity matrix for depth prediction. Specifically, we adopt an efficient linear propagation model, where the propagation is performed with a manner of … raymond devos sketch le rond point
XinJCheng/CSPN: Convolutional Spatial Propagation …
WebGraphCSPN: Geometry-Aware Depth Completion via Dynamic GCNs. This is a PyTorch implementation of the ECCV 2024 paper. [] [Introduction. Image guided depth completion aims to recover per-pixel dense depth maps from sparse depth measurements with the help of aligned color images, which has a wide range of applications from robotics to … WebMar 2, 2024 · As CSPN was successfully applied to depth completion, Park et al. and Cheng et al. further improved CSPN by proposing non-local spatial propagation network and CSPN++, respectively. However, CSPN methods suffer from slow computation time. WebSep 19, 2024 · In practice, we further extend CSPN in two aspects: 1) take a sparse depth map as additional input, which is useful for the task of sparse to dense (a.k.a depth completion); 2) we propose 3D CSPN ... raymond deyoung