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20162023
most citedWould Mega-scale Datasets Further Enhance Spatiotemporal 3D CNNs?

83 citations · 174 across the 7 of their papers we have counts for

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11 papers · 1 filter

cs.CV2023

Estimation of Human Condition at Disaster Site Using Aerial Drone Images

Tomoki Arai, Kenji Iwata, Kensho Hara +1

Drones are being used to assess the situation in various disasters. In this study, we investigate a method to automatically estimate the damage status of people based on their acti…

cs.CV2021

Describing and Localizing Multiple Changes with Transformers

Yue Qiu, Shintaro Yamamoto, Kodai Nakashima +4

Change captioning tasks aim to detect changes in image pairs observed before and after a scene change and generate a natural language description of the changes. Existing change ca…

cs.CV20212 cited

Pre-training without Natural Images

Hirokatsu Kataoka, Kazushige Okayasu, Asato Matsumoto +5

Is it possible to use convolutional neural networks pre-trained without any natural images to assist natural image understanding? The paper proposes a novel concept, Formula-driven…

cs.CV20201 cited

Weakly Supervised Dataset Collection for Robust Person Detection

Munetaka Minoguchi, Ken Okayama, Yutaka Satoh +1

To construct an algorithm that can provide robust person detection, we present a dataset with over 8 million images that was produced in a weakly supervised manner. Through labor-i…

cs.CV202083 cited

Would Mega-scale Datasets Further Enhance Spatiotemporal 3D CNNs?

Hirokatsu Kataoka, Tenga Wakamiya, Kensho Hara +1

How can we collect and use a video dataset to further improve spatiotemporal 3D Convolutional Neural Networks (3D CNNs)? In order to positively answer this open question in video r…

cs.CV2018

Anticipating Traffic Accidents with Adaptive Loss and Large-scale Incident DB

Tomoyuki Suzuki, Hirokatsu Kataoka, Yoshimitsu Aoki +1

In this paper, we propose a novel approach for traffic accident anticipation through (i) Adaptive Loss for Early Anticipation (AdaLEA) and (ii) a large-scale self-annotated inciden…