4 citations · 6 across the 16 of their papers we have counts for
18 papers
MARS-CLIP: Multi-Resolution and Attention Refined Zero-Shot Image Segmentation
Nagito Saito, Shintaro Ito, Koichi Ito +1
Contrastive Language-Image Pre-training (CLIP) has demonstrated impressive capabilities in zero-shot transfer but often struggles with dense prediction tasks due to low spatial res…
DINO-VPT: Hierarchical Visual Prompt Tuning for Joint Physical-Digital Face Anti-Spoofing
Pierre Gallin-Martel, Mika Feng, Koichi Ito +1
With the increasing diversity of spoofing attacks, there is a growing demand for unified Face Anti-Spoofing (FAS) models capable of detecting both physical and digital threats. Whi…
MAGE-Vein: Multi-Instance Age and Gender Estimation from Finger Vein Images
Katsuki Tanaka, Koichi Ito, Takafumi Aoki +4
Age estimation from finger vein images has been widely considered impractical due to severe demographic biases in public datasets and physiological confounding factors like gender.…
PC-Seg: Progressive Cross-View Consistency for 3D OCT Segmentation from Sparse 2D Annotations
Tsubasa Konno, Takahiro Ninomiya, Yukun Zhou +6
Volumetric segmentation of optical coherence tomography (OCT) images is essential for diagnosing ocular diseases but requires labor-intensive voxel-wise annotations. While semi-sup…
G-MASt3R-SfM: Graph-based View Pruning and Multi-stage Optimization for Robust SfM
Toshiki Watanabe, Shintaro Ito, Natsuki Takama +2
Structure from Motion (SfM) is essential for multi-view 3D reconstruction, however, its accuracy heavily relies on the accuracy of image matching. While the recent correspondence m…
PlankFormer: Robust Plankton Instance Segmentation via MAE-Pretrained Vision Transformers and Pseudo Community Image Generation
Masaharu Miyazaki, Yurie Otake, Koichi Ito +3
Plankton monitoring is essential for assessing aquatic ecosystems but is limited by the labor-intensive nature of manual microscopic analysis. Automating the segmentation of plankt…
Benchmarking Vision Foundation Models for Domain-Generalizable Face Anti-Spoofing
Mika Feng, Pierre Gallin-Martel, Koichi Ito +1
Face Anti-Spoofing (FAS) remains challenging due to the requirement for robust domain generalization across unseen environments. While recent trends leverage Vision-Language Models…
Optimizing DINOv2 with Registers for Face Anti-Spoofing
Mika Feng, Pierre Gallin-Martel, Koichi Ito +1
Face recognition systems are designed to be robust against variations in head pose, illumination, and image blur during capture. However, malicious actors can exploit these systems…
Backdoor Poisoning Attack Against Face Spoofing Attack Detection Methods
Shota Iwamatsu, Koichi Ito, Takafumi Aoki
Face recognition systems are robust against environmental changes and noise, and thus may be vulnerable to illegal authentication attempts using user face photos, such as spoofing…
Leveraging Intermediate Features of Vision Transformer for Face Anti-Spoofing
Mika Feng, Koichi Ito, Takafumi Aoki +2
Face recognition systems are designed to be robust against changes in head pose, illumination, and blurring during image capture. If a malicious person presents a face photo of the…
ErpGS: Equirectangular Image Rendering enhanced with 3D Gaussian Regularization
Shintaro Ito, Natsuki Takama, Koichi Ito +2
The use of multi-view images acquired by a 360-degree camera can reconstruct a 3D space with a wide area. There are 3D reconstruction methods from equirectangular images based on N…
Stereo Radargrammetry Using Deep Learning from Airborne SAR Images
Tatsuya Sasayama, Shintaro Ito, Koichi Ito +1
In this paper, we propose a stereo radargrammetry method using deep learning from airborne Synthetic Aperture Radar (SAR) images. Deep learning-based methods are considered to suff…
Sparse2DGS: Sparse-View Surface Reconstruction using 2D Gaussian Splatting with Dense Point Cloud
Natsuki Takama, Shintaro Ito, Koichi Ito +2
Gaussian Splatting (GS) has gained attention as a fast and effective method for novel view synthesis. It has also been applied to 3D reconstruction using multi-view images and can…
Zero-Shot Pseudo Labels Generation Using SAM and CLIP for Semi-Supervised Semantic Segmentation
Nagito Saito, Shintaro Ito, Koichi Ito +1
Semantic segmentation is a fundamental task in medical image analysis and autonomous driving and has a problem with the high cost of annotating the labels required in training. To…
OB3D: A New Dataset for Benchmarking Omnidirectional 3D Reconstruction Using Blender
Shintaro Ito, Natsuki Takama, Toshiki Watanabe +3
Recent advancements in radiance field rendering, exemplified by Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS), have significantly progressed 3D modeling and recons…
Formula-Driven Data Augmentation and Partial Retinal Layer Copying for Retinal Layer Segmentation
Tsubasa Konno, Takahiro Ninomiya, Kanta Miura +5
Major retinal layer segmentation methods from OCT images assume that the retina is flattened in advance, and thus cannot always deal with retinas that have changes in retinal struc…
Fingerprint Feature Extraction by Combining Texture, Minutiae, and Frequency Spectrum Using Multi-Task CNN
Ai Takahashi, Yoshinori Koda, Koichi Ito +1
Although most fingerprint matching methods utilize minutia points and/or texture of fingerprint images as fingerprint features, the frequency spectrum is also a useful feature sinc…
Silhouette-Net: 3D Hand Pose Estimation from Silhouettes
Kuo-Wei Lee, Shih-Hung Liu, Hwann-Tzong Chen +1
3D hand pose estimation has received a lot of attention for its wide range of applications and has made great progress owing to the development of deep learning. Existing approache…