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20182026
most citedDual Residual Networks Leveraging the Potential of Paired Operations for Image Restoration

17 citations · 31 across the 12 of their papers we have counts for

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22 papers · 1 filter

cs.CV2026

Medical-Checklist: Assessing the Comprehension of Medical Images by Multimodal Models

Bannapol Limanond, Masanori Suganuma, Takayuki Okatani

This paper introduces a new benchmark test, Medical-Checklist, for assessing medical multimodal models. The recent advancements in multimodal models have demonstrated significant p…

cs.CV2026

Inverting the Generation Process of Denoising Diffusion Implicit Models: Empirical Evaluation and a Novel Method

Yan Zeng, Masanori Suganuma, Takayuki Okatani

This paper studies the problem of inverting the DDIM image generation process to recover latent variables, particularly the initial noise map, from a generated image. Existing meth…

cs.CV2025

MS-DPPs: Multi-Source Determinantal Point Processes for Contextual Diversity Refinement of Composite Attributes in Text to Image Retrieval

Naoya Sogi, Takashi Shibata, Makoto Terao +2

Result diversification (RD) is a crucial technique in Text-to-Image Retrieval for enhancing the efficiency of a practical application. Conventional methods focus solely on increasi…

cs.CV2025

TB-Bench: Training and Testing Multi-Modal AI for Understanding Spatio-Temporal Traffic Behaviors from Dashcam Images/Videos

Korawat Charoenpitaks, Van-Quang Nguyen, Masanori Suganuma +4

The application of Multi-modal Large Language Models (MLLMs) in Autonomous Driving (AD) faces significant challenges due to their limited training on traffic-specific data and the…

cs.CV2024

Rethinking Annotation for Object Detection: Is Annotating Small-size Instances Worth Its Cost?

Yusuke Hosoya, Masanori Suganuma, Takayuki Okatani

Detecting objects occupying only small areas in an image is difficult, even for humans. Therefore, annotating small-size object instances is hard and thus costly. This study questi…

cs.CV2024

Cascaded Multi-Scale Attention for Enhanced Multi-Scale Feature Extraction and Interaction with Low-Resolution Images

Xiangyong Lu, Masanori Suganuma, Takayuki Okatani

In real-world applications of image recognition tasks, such as human pose estimation, cameras often capture objects, like human bodies, at low resolutions. This scenario poses a ch…