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20182025
most citedOnline Localization and Tracking of Multiple Moving Speakers in Reverberant Environments

48 citations · 140 across the 20 of their papers we have counts for

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12 papers · 1 filter

cs.CV2025★ 3 cited

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2024

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…

cs.CV2022★ 1 cited

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…

cs.CV2021

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…

cs.CV2021★ 12 cited

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…

cs.CV2020★ 3 cited

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…

cs.CV2019★ 25 cited

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.…

cs.CV2018★ 5 cited

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…

cs.CV2018★ 22 cited

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.