6 papers
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…
BEA-GS: BEyond RAdiance Supervision in 3DGS for Precise Object Extraction
Alessio Mazzucchelli, Maria Naranjo-Almeida, Jorge Bustos-Sanchez +4
Most Gaussian Splatting techniques that provide a 3D semantic representation of the scene do not optimize the underlying 3D geometry, making object-level editing or asset extractio…
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…
Movie Facts and Fibs (MF): A Benchmark for Long Movie Understanding
Emmanouil Zaranis, António Farinhas, Saul Santos +28
Despite recent progress in vision-language models (VLMs), holistic understanding of long-form video content remains a significant challenge, partly due to limitations in current be…
Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints
Alberto Maté, Mariella Dimiccoli
This paper proposes a method for long-term action anticipation (LTA), the task of predicting action labels and their duration in a video given the observation of an initial untrimm…
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…