activity
20202026
most citedDeep Feature Tracker: A Novel Application for Deep Convolutional Neural Networks

1 citations · 1 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV2026

Geometry-Consistent Endoscopic Representations for Image-Guided Navigation via Structured Foundation Model Adaptation

Hongchao Shu, Roger D. Soberanis-Mukul, Hao Ding +5

Accurate vision-based navigation in monocular endoscopy is difficult due to limited depth cues, weak tissue texture, non-rigid deformation, and substantial appearance variation acr…

cs.CV2025

BronchOpt : Vision-Based Pose Optimization with Fine-Tuned Foundation Models for Accurate Bronchoscopy Navigation

Hongchao Shu, Roger D. Soberanis-Mukul, Jiru Xu +6

Accurate intra-operative localization of the bronchoscope tip relative to patient anatomy remains challenging due to respiratory motion, anatomical variability, and CT-to-body dive…

cs.CV2021

Cross Your Body: A Cognitive Assessment System for Children

Saif Sayed, Vassilis Athitsos

While many action recognition techniques have great success on public benchmarks, such performance is not necessarily replicated in real-world scenarios, where the data comes from…

cs.CV2021

Hierarchical Modeling for Task Recognition and Action Segmentation in Weakly-Labeled Instructional Videos

Reza Ghoddoosian, Saif Sayed, Vassilis Athitsos

This paper focuses on task recognition and action segmentation in weakly-labeled instructional videos, where only the ordered sequence of video-level actions is available during tr…

cs.CV2021★ 1 cited

Deep Feature Tracker: A Novel Application for Deep Convolutional Neural Networks

Mostafa Parchami, Saif Iftekar Sayed

Feature tracking is the building block of many applications such as visual odometry, augmented reality, and target tracking. Unfortunately, the state-of-the-art vision-based tracki…

cs.CV2020

Action Duration Prediction for Segment-Level Alignment of Weakly-Labeled Videos

Reza Ghoddoosian, Saif Sayed, Vassilis Athitsos

This paper focuses on weakly-supervised action alignment, where only the ordered sequence of video-level actions is available for training. We propose a novel Duration Network, whi…