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Name: First Person Vision @ Image Processing Laboratory - University of Catania
Type: Organization
Location: Catania, Italy
Name: First Person Vision @ Image Processing Laboratory - University of Catania
Type: Organization
Location: Catania, Italy
Implements the loss used in A. Furnari, S. Battiato, G. M. Farinella (2018). Leveraging Uncertainty to Rethink Loss Functions and Evaluation Measures for Egocentric Action Anticipation . In International Workshop on Egocentric Perception, Interaction and Computing (EPIC) in conjunction with ECCV .
Official Detectron2 implementation of DA-RetinaNet of our Image and Vision Computing 2021 work 'An unsupervised domain adaptation scheme for single-stage artwork recognition in cultural sites'
Code for the paper "Differentiable Task Graph Learning: Procedural Activity Representation and Online Mistake Detection from Egocentric Videos"
Action Scene Graphs for Long-Form Understanding of Egocentric Videos (CVPR 2024)
The MECCANO Dataset: official repository in which we provide code and models.
Code for the Paper: Quasi-Online Detection of Take and Release Actions from Egocentric Videos. International Conference on Image Analysis and Processing 2023.
Code for the Paper: Antonino Furnari and Giovanni Maria Farinella. What Would You Expect? Anticipating Egocentric Actions with Rolling-Unrolling LSTMs and Modality Attention. International Conference on Computer Vision, 2019.
Code for the paper: F. Ragusa, G. M. Farinella, A. Furnari. StillFast: An End-to-End Approach for Short-Term Object Interaction Anticipation. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops.
Official Detectron2 implementation of STMDA-RetinaNet of our Computer Vision and Image Understanding 2022 work 'A Multi Camera Unsupervised Domain Adaptation Pipeline for Object Detection in Cultural Sites through Adversarial Learning and Self-Training'
Synchronization is All You Need: Exocentric-to-Egocentric Transfer for Temporal Action Segmentation with Unlabeled Synchronized Video Pairs
Code and documentation of the paper World-map misalignment detection for visual navigation systems
Code of the paper Weakly Supervised Attended Object Detection Using Gaze Data as Annotations
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