most citedDigging Into Normal Incorporated Stereo Matching

6 citations · 9 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2024

VSRD: Instance-Aware Volumetric Silhouette Rendering for Weakly Supervised 3D Object Detection

Zihua Liu, Hiroki Sakuma, Masatoshi Okutomi

Monocular 3D object detection poses a significant challenge in 3D scene understanding due to its inherently ill-posed nature in monocular depth estimation. Existing methods heavily…

cs.CV20241 cited

CFDNet: A Generalizable Foggy Stereo Matching Network with Contrastive Feature Distillation

Zihua Liu, Yizhou Li, Masatoshi Okutomi

Stereo matching under foggy scenes remains a challenging task since the scattering effect degrades the visibility and results in less distinctive features for dense correspondence…

cs.CV2024

Self-Supervised Spatially Variant PSF Estimation for Aberration-Aware Depth-from-Defocus

Zhuofeng Wu, Yusuke Monno, Masatoshi Okutomi

In this paper, we address the task of aberration-aware depth-from-defocus (DfD), which takes account of spatially variant point spread functions (PSFs) of a real camera. To effecti…

cs.CV20246 cited

Digging Into Normal Incorporated Stereo Matching

Zihua Liu, Songyan Zhang, Zhicheng Wang +1

Despite the remarkable progress facilitated by learning-based stereo-matching algorithms, disparity estimation in low-texture, occluded, and bordered regions still remains a bottle…

cs.CV2023

Polarimetric PatchMatch Multi-View Stereo

Jinyu Zhao, Jumpei Oishi, Yusuke Monno +1

PatchMatch Multi-View Stereo (PatchMatch MVS) is one of the popular MVS approaches, owing to its balanced accuracy and efficiency. In this paper, we propose Polarimetric PatchMatch…

cs.CV20232 cited

EMR-MSF: Self-Supervised Recurrent Monocular Scene Flow Exploiting Ego-Motion Rigidity

Zijie Jiang, Masatoshi Okutomi

Self-supervised monocular scene flow estimation, aiming to understand both 3D structures and 3D motions from two temporally consecutive monocular images, has received increasing at…