Publications
Research in generative modeling, computer vision, and 3D understanding.
Selected papers and accompanying resources. Links to project pages, code, and papers are shown when publicly available.
2026
Test-Time Scaling for Safe Text-Guided Image Generation via Intermediate Clean Estimates
Jinya Sakurai, Shueicheng Yan, Xun Xu
A weight-preserving test-time defense for text-to-image diffusion models that detects prohibited concepts from intermediate clean image estimates and intervenes through structured low-rank residual optimization in the text-conditioning space.
FairT2I: Latent Variable Guidance for Training-Free Bias Mitigation with LLM-Assisted Bias Detection
Jinya Sakurai, Yuki Koyama, Issei Sato
FairT2I uses large language models to detect potential social bias in text-to-image generation and rebalances sensitive attributes while preserving generation quality.
OmniDiMM: Bridging 1D, 2D, and 3D with Any-to-Any Multimodal Modeling
Jason Toskov, Oriol Barbany, Rishubh Singh*, Jinya Sakurai, Efe Tarhan, Oğuzhan Fatih Kar, Roman Bachmann, Amir Zadeh, Jesse Allardice, Chuan Li, Carme Torras, Afshin Dehghan, Amir Zamir
An any-to-any multimodal model that bridges 1D, 2D, and 3D representations for generation, retrieval, and object decomposition across text, images, and 3D modalities.
* Equal contribution
2022
Surface Reconstruction from Raw Point Cloud via Energy-Based Models
Jinya Sakurai, Ryutaro Yamauchi, Ryo Furukawa, Tatsushi Matsubayashi
An energy-based approach to learning implicit surface representations from raw point clouds, designed to remain robust in the presence of point noise.
Project and GitHub buttons can be added to the same link row whenever those resources become public.