activity
20162024
most citedHYperbolic Self-Paced Learning for Self-Supervised Skeleton-based Action Representations

11 citations · 19 across the 11 of their papers we have counts for

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5 papers · 1 filter

cs.CV20231 cited

Best Practices for 2-Body Pose Forecasting

Muhammad Rameez Ur Rahman, Luca Scofano, Edoardo De Matteis +3

The task of collaborative human pose forecasting stands for predicting the future poses of multiple interacting people, given those in previous frames. Predicting two people in int…

cs.CV202311 cited

HYperbolic Self-Paced Learning for Self-Supervised Skeleton-based Action Representations

Luca Franco, Paolo Mandica, Bharti Munjal +1

Self-paced learning has been beneficial for tasks where some initial knowledge is available, such as weakly supervised learning and domain adaptation, to select and order the train…

cs.CV20221 cited

CoSMix: Compositional Semantic Mix for Domain Adaptation in 3D LiDAR Segmentation

Cristiano Saltori, Fabio Galasso, Giuseppe Fiameni +3

3D LiDAR semantic segmentation is fundamental for autonomous driving. Several Unsupervised Domain Adaptation (UDA) methods for point cloud data have been recently proposed to impro…

cs.CV2022

GIPSO: Geometrically Informed Propagation for Online Adaptation in 3D LiDAR Segmentation

Cristiano Saltori, Evgeny Krivosheev, Stéphane Lathuilière +5

3D point cloud semantic segmentation is fundamental for autonomous driving. Most approaches in the literature neglect an important aspect, i.e., how to deal with domain shift when…

cs.CV2016

Towards Segmenting Consumer Stereo Videos: Benchmark, Baselines and Ensembles

Wei-Chen Chiu, Fabio Galasso, Mario Fritz

Are we ready to segment consumer stereo videos? The amount of this data type is rapidly increasing and encompasses rich information of appearance, motion and depth cues. However, t…