activity
20232026
most citedA Survey on Deep Learning Techniques for Action Anticipation

2 citations · 3 across the 11 of their papers we have counts for

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5 papers · 1 filter

cs.CV2025

Looking into the Unknown: Exploring Action Discovery for Segmentation of Known and Unknown Actions

Federico Spurio, Emad Bahrami, Olga Zatsarynna +3

We introduce Action Discovery, a novel setup within Temporal Action Segmentation that addresses the challenge of defining and annotating ambiguous actions and incomplete annotation…

cs.RO2025

Privacy-Preserving Semantic Segmentation from Ultra-Low-Resolution RGB Inputs

Xuying Huang, Sicong Pan, Olga Zatsarynna +2

RGB-based semantic segmentation has become a mainstream approach for visual perception and is widely applied in a variety of downstream tasks. However, existing methods typically r…

cs.CV2025

Towards Generalizing Temporal Action Segmentation to Unseen Views

Emad Bahrami, Olga Zatsarynna, Gianpiero Francesca +1

While there has been substantial progress in temporal action segmentation, the challenge to generalize to unseen views remains unaddressed. Hence, we define a protocol for unseen v…

cs.CV2025

Hierarchical Vector Quantization for Unsupervised Action Segmentation

Federico Spurio, Emad Bahrami, Gianpiero Francesca +1

In this work, we address unsupervised temporal action segmentation, which segments a set of long, untrimmed videos into semantically meaningful segments that are consistent across…

cs.CV2025

MANTA: Diffusion Mamba for Efficient and Effective Stochastic Long-Term Dense Anticipation

Olga Zatsarynna, Emad Bahrami, Yazan Abu Farha +2

Long-term dense action anticipation is very challenging since it requires predicting actions and their durations several minutes into the future based on provided video observation…