24 citations · 48 across the 4 of their papers we have counts for
6 papers
When to Laugh and How Hard? A Multimodal Approach to Detecting Humor and its Intensity
Khalid Alnajjar, Mika Hämäläinen, Jörg Tiedemann +2
Prerecorded laughter accompanying dialog in comedy TV shows encourages the audience to laugh by clearly marking humorous moments in the show. We present an approach for automatical…
Tackling the Unannotated: Scene Graph Generation with Bias-Reduced Models
Tzu-Jui Julius Wang, Selen Pehlivan, Jorma Laaksonen
Predicting a scene graph that captures visual entities and their interactions in an image has been considered a crucial step towards full scene comprehension. Recent scene graph ge…
Deep Contextual Attention for Human-Object Interaction Detection
Tiancai Wang, Rao Muhammad Anwer, Muhammad Haris Khan +4
Human-object interaction detection is an important and relatively new class of visual relationship detection tasks, essential for deeper scene understanding. Most existing approach…
Character-Centric Storytelling
Aditya Surikuchi, Jorma Laaksonen
Sequential vision-to-language or visual storytelling has recently been one of the areas of focus in computer vision and language modeling domains. Though existing models generate n…
The MeMAD Submission to the WMT18 Multimodal Translation Task
Stig-Arne Grönroos, Benoit Huet, Mikko Kurimo +8
This paper describes the MeMAD project entry to the WMT Multimodal Machine Translation Shared Task. We propose adapting the Transformer neural machine translation (NMT) architectur…
Saliency Revisited: Analysis of Mouse Movements versus Fixations
Hamed R. Tavakoli, Fawad Ahmed, Ali Borji +1
This paper revisits visual saliency prediction by evaluating the recent advancements in this field such as crowd-sourced mouse tracking-based databases and contextual annotations.…