57 citations · 97 across the 10 of their papers we have counts for
14 papers
Relevance-based Margin for Contrastively-trained Video Retrieval Models
Alex Falcon, Swathikiran Sudhakaran, Giuseppe Serra +2
Video retrieval using natural language queries has attracted increasing interest due to its relevance in real-world applications, from intelligent access in private media galleries…
SAIC_Cambridge-HuPBA-FBK Submission to the EPIC-Kitchens-100 Action Recognition Challenge 2021
Swathikiran Sudhakaran, Adrian Bulat, Juan-Manuel Perez-Rua +5
This report presents the technical details of our submission to the EPIC-Kitchens-100 Action Recognition Challenge 2021. To participate in the challenge we deployed spatio-temporal…
Space-time Mixing Attention for Video Transformer
Adrian Bulat, Juan-Manuel Perez-Rua, Swathikiran Sudhakaran +2
This paper is on video recognition using Transformers. Very recent attempts in this area have demonstrated promising results in terms of recognition accuracy, yet they have been al…
Learning to Recognize Actions on Objects in Egocentric Video with Attention Dictionaries
Swathikiran Sudhakaran, Sergio Escalera, Oswald Lanz
We present EgoACO, a deep neural architecture for video action recognition that learns to pool action-context-object descriptors from frame level features by leveraging the verb-no…
FBK-HUPBA Submission to the EPIC-Kitchens Action Recognition 2020 Challenge
Swathikiran Sudhakaran, Sergio Escalera, Oswald Lanz
In this report we describe the technical details of our submission to the EPIC-Kitchens Action Recognition 2020 Challenge. To participate in the challenge we deployed spatio-tempor…
Gate-Shift Networks for Video Action Recognition
Swathikiran Sudhakaran, Sergio Escalera, Oswald Lanz
Deep 3D CNNs for video action recognition are designed to learn powerful representations in the joint spatio-temporal feature space. In practice however, because of the large numbe…