4 citations · 6 across the 12 of their papers we have counts for
12 papers
SEGAR: Selective Enhancement for Generative Augmented Reality
Fanjun Bu, Chenyang Yuan, Hiroshi Yasuda
Generative world models offer a compelling foundation for augmented-reality (AR) applications: by predicting future image sequences that incorporate deliberate visual edits, they e…
Using Vision-Language Models as Proxies for Social Intelligence in Human-Robot Interaction
Fanjun Bu, Melina Tsai, Audrey Tjokro +3
Robots operating in everyday environments must often decide when and whether to engage with people, yet such decisions often hinge on subtle nonverbal cues that unfold over time an…
The Robotability Score: Enabling Harmonious Robot Navigation on Urban Streets
Matt Franchi, Maria Teresa Parreira, Fanjun Bu +1
This paper introduces the Robotability Score (), a novel metric that quantifies the suitability of urban environments for autonomous robot navigation. Through expert interviews…
Making Sense of Robots in Public Spaces: A Study of Trash Barrel Robots
Fanjun Bu, Kerstin Fischer, Wendy Ju
In this work, we analyze video data and interviews from a public deployment of two trash barrel robots in a large public space to better understand the sensemaking activities peopl…
ReStory: VLM-augmentation of Social Human-Robot Interaction Datasets
Fanjun Bu, Wendy Ju
Internet-scaled datasets are a luxury for human-robot interaction (HRI) researchers, as collecting natural interaction data in the wild is time-consuming and logistically challengi…
Boosting Visual Fidelity in Driving Simulations through Diffusion Models
Fanjun Bu, Hiroshi Yasuda
Diffusion models have made substantial progress in facilitating image generation and editing. As the technology matures, we see its potential in the context of driving simulations…
Field Notes on Deploying Research Robots in Public Spaces
Fanjun Bu, Alexandra Bremers, Mark Colley +1
Human-robot interaction requires to be studied in the wild. In the summers of 2022 and 2023, we deployed two trash barrel service robots through the wizard-of-oz protocol in public…
SSUP-HRI: Social Signaling in Urban Public Human-Robot Interaction dataset
Fanjun Bu, Wendy Ju
This paper introduces our dataset featuring human-robot interactions (HRI) in urban public environments. This dataset is rich with social signals that we believe can be modeled to…
Portobello: Extending Driving Simulation from the Lab to the Road
Fanjun Bu, Stacey Li, David Goedicke +4
In automotive user interface design, testing often starts with lab-based driving simulators and migrates toward on-road studies to mitigate risks. Mixed reality (XR) helps translat…
Human-Robot Commensality: Bite Timing Prediction for Robot-Assisted Feeding in Groups
Jan Ondras, Abrar Anwar, Tong Wu +4
We develop data-driven models to predict when a robot should feed during social dining scenarios. Being able to eat independently with friends and family is considered one of the m…
Consequences of Slow Neural Dynamics for Incremental Learning
Shima Rahimi Moghaddam, Fanjun Bu, Christopher J. Honey
In the human brain, internal states are often correlated over time (due to local recurrence and other intrinsic circuit properties), punctuated by abrupt transitions. At first glan…
Object Permanence Through Audio-Visual Representations
Fanjun Bu, Chien-Ming Huang
As robots perform manipulation tasks and interact with objects, it is probable that they accidentally drop objects (e.g., due to an inadequate grasp of an unfamiliar object) that s…