activity
20222026
most citedLimeCross: Context-Conditioned Layered Image Editing with Structural Consistency

2 citations · 3 across the 13 of their papers we have counts for

collaborators

14 papers

cs.CV2026

Where Did the Light Come From? Diagnosing Cast-Shadow Reasoning in VLMs and Borrowing the Missing Shadow Prior from Image Generation Models

Ryugo Morita, Shunsuke Kitada, Stanislav Frolov +5

Shadows are observable consequences of latent physical causes, arising from the interaction between illumination, object geometry, and scene structure. A model that understands sha…

cs.CV2026

Astrolabe: Spherical-Map Guidance Across Diffusion Pipelines for Full-Body Capture from Unconstrained Images

Shuliang Zhu, Qi Wang, Ryugo Morita +1

Full-body capture from unconstrained photographs requires global correspondence across arbitrary views, poses, crops, and occlusions. Yet pose, geometry, and foundation features es…

cs.CV2026★ 2 cited

LimeCross: Context-Conditioned Layered Image Editing with Structural Consistency

Ryugo Morita, Stanislav Frolov, Brian Bernhard Moser +4

Layered image assets are widely used in real-world creative workflows, enabling non-destructive iteration and flexible re-composition. Recent advances in layered image generation a…

cs.CV2026

LGTM: Training-Free Light-Guided Text-to-Image Diffusion Model via Initial Noise Manipulation

Ryugo Morita, Stanislav Frolov, Brian Bernhard Moser +3

Diffusion models have demonstrated high-quality performance in conditional text-to-image generation, particularly with structural cues such as edges, layouts, and depth. However, l…

cs.CV2025

TAUE: Training-free Noise Transplant and Cultivation Diffusion Model

Daichi Nagai, Ryugo Morita, Shunsuke Kitada +1

Despite the remarkable success of text-to-image diffusion models, their output of a single, flattened image remains a critical bottleneck for professional applications requiring la…

eess.IV2025

Audio-Visual Driven Compression for Low-Bitrate Talking Head Videos

Riku Takahashi, Ryugo Morita, Jinjia Zhou

Talking head video compression has advanced with neural rendering and keypoint-based methods, but challenges remain, especially at low bit rates, including handling large head move…

eess.IV2025

Bidirectional Learned Facial Animation Codec for Low Bitrate Talking Head Videos

Riku Takahashi, Ryugo Morita, Fuma Kimishima +2

Existing deep facial animation coding techniques efficiently compress talking head videos by applying deep generative models. Instead of compressing the entire video sequence, thes…

cs.HC2025★ 1 cited

GenAIReading: Augmenting Human Cognition with Interactive Digital Textbooks Using Large Language Models and Image Generation Models

Ryugo Morita, Ko Watanabe, Jinjia Zhou +2

Cognitive augmentation is a cornerstone in advancing education, particularly through personalized learning. However, personalizing extensive textual materials, such as narratives a…

cs.CV2024

Block based Adaptive Compressive Sensing with Sampling Rate Control

Kosuke Iwama, Ryugo Morita, Jinjia Zhou

Compressive sensing (CS), acquiring and reconstructing signals below the Nyquist rate, has great potential in image and video acquisition to exploit data redundancy and greatly red…

cs.CV2024

Visual question answering based evaluation metrics for text-to-image generation

Mizuki Miyamoto, Ryugo Morita, Jinjia Zhou

Text-to-image generation and text-guided image manipulation have received considerable attention in the field of image generation tasks. However, the mainstream evaluation methods…

cs.CV2024

TKG-DM: Training-free Chroma Key Content Generation Diffusion Model

Ryugo Morita, Stanislav Frolov, Brian Bernhard Moser +4

Diffusion models have enabled the generation of high-quality images with a strong focus on realism and textual fidelity. Yet, large-scale text-to-image models, such as Stable Diffu…

eess.IV2024

Edge-based Denoising Image Compression

Ryugo Morita, Hitoshi Nishimura, Ko Watanabe +2

In recent years, deep learning-based image compression, particularly through generative models, has emerged as a pivotal area of research. Despite significant advancements, challen…

cs.CV2023

BATINet: Background-Aware Text to Image Synthesis and Manipulation Network

Ryugo Morita, Zhiqiang Zhang, Jinjia Zhou

Background-Induced Text2Image (BIT2I) aims to generate foreground content according to the text on the given background image. Most studies focus on generating high-quality foregro…

cs.CV2022

Interactive Image Manipulation with Complex Text Instructions

Ryugo Morita, Zhiqiang Zhang, Man M. Ho +1

Recently, text-guided image manipulation has received increasing attention in the research field of multimedia processing and computer vision due to its high flexibility and contro…