48 citations · 140 across the 20 of their papers we have counts for
21 papers
OSGym: Scalable OS Infra for Computer Use Agents
Zengyi Qin, Jinyuan Chen, Yunze Man +25
Training computer use agents requires full-featured OS sandboxes with GUI environments, which consume substantial hardware resources as the number of sandboxes scales. Stochastic e…
Generalizable Coarse-to-Fine Robot Manipulation via Language-Aligned 3D Keypoints
Jianshu Hu, Lidi Wang, Shujia Li +4
Hierarchical coarse-to-fine policy, where a coarse branch predicts a region of interest to guide a fine-grained action predictor, has demonstrated significant potential in robotic…
The SAGES Critical View of Safety Challenge: A Global Benchmark for AI-Assisted Surgical Quality Assessment
Deepak Alapatt, Jennifer Eckhoff, Zhiliang Lyu +38
Advances in artificial intelligence (AI) for surgical quality assessment promise to democratize access to expertise, with applications in training, guidance, and accreditation. Thi…
Holistic Surgical Phase Recognition with Hierarchical Input Dependent State Space Models
Haoyang Wu, Tsun-Hsuan Wang, Mathias Lechner +7
Surgical workflow analysis is essential in robot-assisted surgeries, yet the long duration of such procedures poses significant challenges for comprehensive video analysis. Recent…
GenHOI: Generalizing Text-driven 4D Human-Object Interaction Synthesis for Unseen Objects
Shujia Li, Haiyu Zhang, Xinyuan Chen +2
While diffusion models and large-scale motion datasets have advanced text-driven human motion synthesis, extending these advances to 4D human-object interaction (HOI) remains chall…
Tracking-Aware Deformation Field Estimation for Non-rigid 3D Reconstruction in Robotic Surgeries
Zeqing Wang, Han Fang, Yihong Xu +1
Minimally invasive procedures have been advanced rapidly by the robotic laparoscopic surgery. The latter greatly assists surgeons in sophisticated and precise operations with reduc…
INViT: A Generalizable Routing Problem Solver with Invariant Nested View Transformer
Han Fang, Zhihao Song, Paul Weng +1
Recently, deep reinforcement learning has shown promising results for learning fast heuristics to solve routing problems. Meanwhile, most of the solvers suffer from generalizing to…
Hypergraph-Transformer (HGT) for Interactive Event Prediction in Laparoscopic and Robotic Surgery
Lianhao Yin, Yutong Ban, Jennifer Eckhoff +3
Understanding and anticipating intraoperative events and actions is critical for intraoperative assistance and decision-making during minimally invasive surgery. Automated predicti…
Drive Anywhere: Generalizable End-to-end Autonomous Driving with Multi-modal Foundation Models
Tsun-Hsuan Wang, Alaa Maalouf, Wei Xiao +5
As autonomous driving technology matures, end-to-end methodologies have emerged as a leading strategy, promising seamless integration from perception to control via deep learning.…
Infrastructure-based End-to-End Learning and Prevention of Driver Failure
Noam Buckman, Shiva Sreeram, Mathias Lechner +4
Intelligent intersection managers can improve safety by detecting dangerous drivers or failure modes in autonomous vehicles, warning oncoming vehicles as they approach an intersect…
On the Forward Invariance of Neural ODEs
Wei Xiao, Tsun-Hsuan Wang, Ramin Hasani +4
We propose a new method to ensure neural ordinary differential equations (ODEs) satisfy output specifications by using invariance set propagation. Our approach uses a class of cont…
Concept Graph Neural Networks for Surgical Video Understanding
Yutong Ban, Jennifer A. Eckhoff, Thomas M. Ward +4
We constantly integrate our knowledge and understanding of the world to enhance our interpretation of what we see. This ability is crucial in application domains which entail reaso…
SUPR-GAN: SUrgical PRediction GAN for Event Anticipation in Laparoscopic and Robotic Surgery
Yutong Ban, Guy Rosman, Jennifer A. Eckhoff +6
Comprehension of surgical workflow is the foundation upon which artificial intelligence (AI) and machine learning (ML) holds the potential to assist intraoperative decision-making…
TransCenter: Transformers with Dense Representations for Multiple-Object Tracking
Yihong Xu, Yutong Ban, Guillaume Delorme +3
Transformers have proven superior performance for a wide variety of tasks since they were introduced. In recent years, they have drawn attention from the vision community in tasks…
Aggregating Long-Term Context for Learning Laparoscopic and Robot-Assisted Surgical Workflows
Yutong Ban, Guy Rosman, Thomas Ward +5
Analyzing surgical workflow is crucial for surgical assistance robots to understand surgeries. With the understanding of the complete surgical workflow, the robots are able to assi…
How To Train Your Deep Multi-Object Tracker
Yihong Xu, Aljosa Osep, Yutong Ban +3
The recent trend in vision-based multi-object tracking (MOT) is heading towards leveraging the representational power of deep learning to jointly learn to detect and track objects.…
A cascaded multiple-speaker localization and tracking system
Xiaofei Li, Yutong Ban, Laurent Girin +2
This paper presents an online multiple-speaker localization and tracking method, as the INRIA-Perception contribution to the LOCATA Challenge 2018. First, the recursive least-squar…
Tracking Multiple Audio Sources with the von Mises Distribution and Variational EM
Yutong Ban, Xavier Alameda-PIneda, Christine Evers +1
In this paper we address the problem of simultaneously tracking several moving audio sources, namely the problem of estimating source trajectories from a sequence of observed featu…
Variational Bayesian Inference for Audio-Visual Tracking of Multiple Speakers
Yutong Ban, Xavier Alameda-Pineda, Laurent Girin +1
In this paper we address the problem of tracking multiple speakers via the fusion of visual and auditory information. We propose to exploit the complementary nature of these two mo…
Online Localization and Tracking of Multiple Moving Speakers in Reverberant Environments
Xiaofei Li, Yutong Ban, Laurent Girin +2
We address the problem of online localization and tracking of multiple moving speakers in reverberant environments. The paper has the following contributions. We use the direct-pat…
A Deep Network for Arousal-Valence Emotion Prediction with Acoustic-Visual Cues
Songyou Peng, Le Zhang, Yutong Ban +2
In this paper, we comprehensively describe the methodology of our submissions to the One-Minute Gradual-Emotion Behavior Challenge 2018.