activity
20192026
most citedMissing Data Imputation with Adversarially-trained Graph Convolutional Networks

186 citations · 451 across the 24 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

cs.CV2024

Social EgoMesh Estimation

Luca Scofano, Alessio Sampieri, Edoardo De Matteis +2

Accurately estimating the 3D pose of the camera wearer in egocentric video sequences is crucial to modeling human behavior in virtual and augmented reality applications. The task p…

cs.CV2024

OVOSE: Open-Vocabulary Semantic Segmentation in Event-Based Cameras

Muhammad Rameez Ur Rahman, Jhony H. Giraldo, Indro Spinelli +2

Event cameras, known for low-latency operation and superior performance in challenging lighting conditions, are suitable for sensitive computer vision tasks such as semantic segmen…

cs.CV2024★ 2 cited

Length-Aware Motion Synthesis via Latent Diffusion

Alessio Sampieri, Alessio Palma, Indro Spinelli +1

The target duration of a synthesized human motion is a critical attribute that requires modeling control over the motion dynamics and style. Speeding up an action performance is no…

cs.CV2024

MoDiPO: text-to-motion alignment via AI-feedback-driven Direct Preference Optimization

Massimiliano Pappa, Luca Collorone, Giovanni Ficarra +2

Diffusion Models have revolutionized the field of human motion generation by offering exceptional generation quality and fine-grained controllability through natural language condi…

cs.RO2024

Following the Human Thread in Social Navigation

Luca Scofano, Alessio Sampieri, Tommaso Campari +4

The success of collaboration between humans and robots in shared environments relies on the robot's real-time adaptation to human motion. Specifically, in Social Navigation, the ag…

cs.LG2024★ 2 cited

TopoX: A Suite of Python Packages for Machine Learning on Topological Domains

Mustafa Hajij, Mathilde Papillon, Florian Frantzen +40

We introduce TopoX, a Python software suite that provides reliable and user-friendly building blocks for computing and machine learning on topological domains that extend graphs: h…