activity
20232026
most citedCLOT: Closed Loop Optimal Transport for Unsupervised Action Segmentation

3 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

D-CLOT: Double Closed Loop Optimal Transport for Unsupervised Action Segmentation

Elena Bueno-Benito, Mariella Dimiccoli

Optimal transport (OT) has emerged as an effective framework for unsupervised action segmentation. Yet, in existing OT-based methods, the latent action prototypes that define the O…

cs.CV2025★ 3 cited

CLOT: Closed Loop Optimal Transport for Unsupervised Action Segmentation

Elena Bueno-Benito, Mariella Dimiccoli

Unsupervised action segmentation has recently pushed its limits with ASOT, an optimal transport (OT)-based method that simultaneously learns action representations and performs clu…

cs.CV2025

How Well Do Vision-Language Models Understand Movies?

Emmanouil Zaranis, António Farinhas, Saul Santos +28

Vision-language models (VLMs) can increasingly handle extended contexts and answer questions about long videos--but can they understand the narrative structure of movies as humans…

cs.CV2024★ 1 cited

2by2: Weakly-Supervised Learning for Global Action Segmentation

Elena Bueno-Benito, Mariella Dimiccoli

This paper presents a simple yet effective approach for the poorly investigated task of global action segmentation, aiming at grouping frames capturing the same action across video…

cs.CV2023★ 1 cited

Leveraging triplet loss for unsupervised action segmentation

E. Bueno-Benito, B. Tura, M. Dimiccoli

In this paper, we propose a novel fully unsupervised framework that learns action representations suitable for the action segmentation task from the single input video itself, with…