activity
20172023
most citedCholecTriplet2022: Show me a tool and tell me the triplet -- an endoscopic vision challenge for surgical action triplet detection

42 citations · 71 across the 12 of their papers we have counts for

collaborators

14 papers

eess.IV2023★ 42 cited

CholecTriplet2022: Show me a tool and tell me the triplet -- an endoscopic vision challenge for surgical action triplet detection

Chinedu Innocent Nwoye, Tong Yu, Saurav Sharma +46

Formalizing surgical activities as triplets of the used instruments, actions performed, and target anatomies is becoming a gold standard approach for surgical activity modeling. Th…

eess.IV2022

Placental Vessel Segmentation and Registration in Fetoscopy: Literature Review and MICCAI FetReg2021 Challenge Findings

Sophia Bano, Alessandro Casella, Francisco Vasconcelos +28

Fetoscopy laser photocoagulation is a widely adopted procedure for treating Twin-to-Twin Transfusion Syndrome (TTTS). The procedure involves photocoagulation pathological anastomos…

eess.IV2022★ 3 cited

Histogram of Oriented Gradients Meet Deep Learning: A Novel Multi-task Deep Network for Medical Image Semantic Segmentation

Binod Bhattarai, Ronast Subedi, Rebati Raman Gaire +2

We present our novel deep multi-task learning method for medical image segmentation. Existing multi-task methods demand ground truth annotations for both the primary and auxiliary…

cs.CV2020

FairFace Challenge at ECCV 2020: Analyzing Bias in Face Recognition

Tomáš Sixta, Julio C. S. Jacques Junior, Pau Buch-Cardona +3

This work summarizes the 2020 ChaLearn Looking at People Fair Face Recognition and Analysis Challenge and provides a description of the top-winning solutions and analysis of the re…

cs.CV2019★ 2 cited

Filtering Point Targets via Online Learning of Motion Models

Mehryar Emambakhsh, Alessandro Bay, Eduard Vazquez

Filtering point targets in highly cluttered and noisy data frames can be very challenging, especially for complex target motions. Fixed motion models can fail to provide accurate p…

cs.CV2019

Real-time tracker with fast recovery from target loss

Alessandro Bay, Panagiotis Sidiropoulos, Eduard Vazquez +1

In this paper, we introduce a variation of a state-of-the-art real-time tracker (CFNet), which adds to the original algorithm robustness to target loss without a significant comput…