most citedMATIS: Masked-Attention Transformers for Surgical Instrument Segmentation

28 citations · 35 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2023★ 5 cited

STRIDE: Street View-based Environmental Feature Detection and Pedestrian Collision Prediction

Cristina González, Nicolás Ayobi, Felipe Escallón +8

This paper introduces a novel benchmark to study the impact and relationship of built environment elements on pedestrian collision prediction, intending to enhance environmental aw…

cs.AI2023

Guarding the Guardians: Automated Analysis of Online Child Sexual Abuse

Juanita Puentes, Angela Castillo, Wilmar Osejo +5

Online violence against children has increased globally recently, demanding urgent attention. Competent authorities manually analyze abuse complaints to comprehend crime dynamics a…

cs.CV2023

EgoCOL: Egocentric Camera pose estimation for Open-world 3D object Localization @Ego4D challenge 2023

Cristhian Forigua, Maria Escobar, Jordi Pont-Tuset +2

We present EgoCOL, an egocentric camera pose estimation method for open-world 3D object localization. Our method leverages sparse camera pose reconstructions in a two-fold manner,…

cs.CV2023★ 1 cited

BoDiffusion: Diffusing Sparse Observations for Full-Body Human Motion Synthesis

Angela Castillo, Maria Escobar, Guillaume Jeanneret +4

Mixed reality applications require tracking the user's full-body motion to enable an immersive experience. However, typical head-mounted devices can only track head and hand moveme…

eess.IV2023

JoB-VS: Joint Brain-Vessel Segmentation in TOF-MRA Images

Natalia Valderrama, Ioannis Pitsiorlas, Luisa Vargas +2

We propose the first joint-task learning framework for brain and vessel segmentation (JoB-VS) from Time-of-Flight Magnetic Resonance images. Unlike state-of-the-art vessel segmenta…

cs.CV2023★ 28 cited

MATIS: Masked-Attention Transformers for Surgical Instrument Segmentation

Nicolás Ayobi, Alejandra Pérez-Rondón, Santiago Rodríguez +1

We propose Masked-Attention Transformers for Surgical Instrument Segmentation (MATIS), a two-stage, fully transformer-based method that leverages modern pixel-wise attention mechan…

cs.CV2022★ 1 cited

Video Swin Transformers for Egocentric Video Understanding @ Ego4D Challenges 2022

Maria Escobar, Laura Daza, Cristina González +2

We implemented Video Swin Transformer as a base architecture for the tasks of Point-of-No-Return temporal localization and Object State Change Classification. Our method achieved c…