29 citations · 54 across the 16 of their papers we have counts for
9 papers · 1 filter
MulCPred: Learning Multi-modal Concepts for Explainable Pedestrian Action Prediction
Yan Feng, Alexander Carballo, Keisuke Fujii +3
Pedestrian action prediction is of great significance for many applications such as autonomous driving. However, state-of-the-art methods lack explainability to make trustworthy pr…
DRUformer: Enhancing the driving scene Important object detection with driving relationship self-understanding
Yingjie Niu, Ming Ding, Keisuke Fujii +3
Traffic accidents frequently lead to fatal injuries, contributing to over 50 million deaths until 2023. To mitigate driving hazards and ensure personal safety, it is crucial to ass…
Runner re-identification from single-view running video in the open-world setting
Tomohiro Suzuki, Kazushi Tsutsui, Kazuya Takeda +1
In many sports, player re-identification is crucial for automatic video processing and analysis. However, most of the current studies on player re-identification in multi- or singl…
Compositional Semantics for Open Vocabulary Spatio-semantic Representations
Robin Karlsson, Francisco Lepe-Salazar, Kazuya Takeda
Vision-language models (VLMs) transform environment percepts into vision-language semantics interpretable by LLMs. However, completing complex tasks often requires reasoning about…
Estimation of control area in badminton doubles with pose information from top and back view drone videos
Ning Ding, Kazuya Takeda, Wenhui Jin +2
The application of visual tracking to the performance analysis of sports players in dynamic competitions is vital for effective coaching. In doubles matches, coordinated positionin…
Learning to Predict Navigational Patterns from Partial Observations
Robin Karlsson, Alexander Carballo, Francisco Lepe-Salazar +3
Human beings cooperatively navigate rule-constrained environments by adhering to mutually known navigational patterns, which may be represented as directional pathways or road lane…
Predictive World Models from Real-World Partial Observations
Robin Karlsson, Alexander Carballo, Keisuke Fujii +2
Cognitive scientists believe adaptable intelligent agents like humans perform reasoning through learned causal mental simulations of agents and environments. The problem of learnin…
Automatic detection of faults in race walking from a smartphone camera: a comparison of an Olympic medalist and university athletes
Tomohiro Suzuki, Kazuya Takeda, Keisuke Fujii
Automatic fault detection is a major challenge in many sports. In race walking, referees visually judge faults according to the rules. Hence, ensuring objectivity and fairness whil…
ViCE: Improving Dense Representation Learning by Superpixelization and Contrasting Cluster Assignment
Robin Karlsson, Tomoki Hayashi, Keisuke Fujii +3
Recent self-supervised models have demonstrated equal or better performance than supervised methods, opening for AI systems to learn visual representations from practically unlimit…