1 citations · 1 across the 15 of their papers we have counts for
17 papers
Virtual Chromoendscopy with Tunable Visibility Enhancement
Yuhi Kanno, Yusuke Monno, Sho Suzuki +2
Chromoendoscopy (CE) is a common clinical practice that sprays indigo carmine blue dye onto the gastric surface to improve the visibility of gastric lesions, such as an early cance…
StereoSplat+: Feed-Forward Stereo Gaussian Splatting with Diffusion-Assisted Progressive Inference
Zihua Liu, Masatoshi Okutomi
Recent advances in 3D Gaussian Splatting (3DGS) have enabled high-quality, render-ready scene representations for novel-view synthesis. However, most existing 3DGS pipelines rely o…
Gastroendoscopy View Synthesis: A New Real Dataset and Evaluation
Masaki Minai, Yusuke Monno, Masatoshi Okutomi +1
Novel view synthesis (NVS) is an active research topic in computer vision, owing to the success of neural radiance field (NeRF) and 3D Gaussian splatting (3DGS) methods. While NVS…
Stochastic Signed Distance Processes
Hiroki Sakuma, Masatoshi Okutomi
Multi-view surface reconstruction is a core problem in computer vision. One prominent line of work represents the surface implicitly as a signed distance field (SDF), optimizing it…
Leveraging NeRF-Rendered Images for 3D Gaussian Splatting
Mizuki Morikawa, Yuta Shimizu, Chunyu Li +2
Neural radiance field (NeRF) and 3D Gaussian splatting (3DGS) are two mainstream approaches for novel view synthesis. They often show complementary performance, i.e., 3DGS demonstr…
VSRD++: Autolabeling for 3D Object Detection via Instance-Aware Volumetric Silhouette Rendering
Zihua Liu, Hiroki Sakuma, Masatoshi Okutomi
Monocular 3D object detection is a fundamental yet challenging task in 3D scene understanding. Existing approaches heavily depend on supervised learning with extensive 3D annotatio…
DMS:Diffusion-Based Multi-Baseline Stereo Generation for Improving Self-Supervised Depth Estimation
Zihua Liu, Yizhou Li, Songyan Zhang +1
While supervised stereo matching and monocular depth estimation have advanced significantly with learning-based algorithms, self-supervised methods using stereo images as supervisi…
Segmentation-Guided Neural Radiance Fields for Novel Street View Synthesis
Yizhou Li, Yusuke Monno, Masatoshi Okutomi +3
Recent advances in Neural Radiance Fields (NeRF) have shown great potential in 3D reconstruction and novel view synthesis, particularly for indoor and small-scale scenes. However,…
TDM: Temporally-Consistent Diffusion Model for All-in-One Real-World Video Restoration
Yizhou Li, Zihua Liu, Yusuke Monno +1
In this paper, we propose the first diffusion-based all-in-one video restoration method that utilizes the power of a pre-trained Stable Diffusion and a fine-tuned ControlNet. Our m…
Disparity Estimation Using a Quad-Pixel Sensor
Zhuofeng Wu, Doehyung Lee, Zihua Liu +3
A quad-pixel (QP) sensor is increasingly integrated into commercial mobile cameras. The QP sensor has a unit of 22 four photodiodes under a single microlens, generating mul…
Neural Radiance Fields for Novel View Synthesis in Monocular Gastroscopy
Zijie Jiang, Yusuke Monno, Masatoshi Okutomi +2
Enabling the synthesis of arbitrarily novel viewpoint images within a patient's stomach from pre-captured monocular gastroscopic images is a promising topic in stomach diagnosis. T…
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…
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…
Reflection Removal Using Recurrent Polarization-to-Polarization Network
Wenjiao Bian, Yusuke Monno, Masatoshi Okutomi
This paper addresses reflection removal, which is the task of separating reflection components from a captured image and deriving the image with only transmission components. Consi…
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…
Global Occlusion-Aware Transformer for Robust Stereo Matching
Zihua Liu, Yizhou Li, Masatoshi Okutomi
Despite the remarkable progress facilitated by learning-based stereo-matching algorithms, the performance in the ill-conditioned regions, such as the occluded regions, remains a bo…
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…