activity
20192026
most citedIdentifying Visible Actions in Lifestyle Vlogs

10 citations · 31 across the 16 of their papers we have counts for

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5 papers · 1 filter

cs.CV2025

When Cultures Meet: Multicultural Text-to-Image Generation

Parth Bhalerao, Mounika Yalamarty, Brian Trinh +1

Text-to-image generation models have achieved strong performance in culturally homogeneous settings, yet their ability to generate multicultural scenes, where people and landmarks…

cs.CV2024

The Power of Many: Multi-Agent Multimodal Models for Cultural Image Captioning

Longju Bai, Angana Borah, Oana Ignat +1

Large Multimodal Models (LMMs) exhibit impressive performance across various multimodal tasks. However, their effectiveness in cross-cultural contexts remains limited due to the pr…

cs.CV2024

CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark

David Romero, Chenyang Lyu, Haryo Akbarianto Wibowo +73

Visual Question Answering (VQA) is an important task in multimodal AI, and it is often used to test the ability of vision-language models to understand and reason on knowledge pres…

cs.CV2021

WhyAct: Identifying Action Reasons in Lifestyle Vlogs

Oana Ignat, Santiago Castro, Hanwen Miao +2

We aim to automatically identify human action reasons in online videos. We focus on the widespread genre of lifestyle vlogs, in which people perform actions while verbally describi…

cs.CV2021

FIBER: Fill-in-the-Blanks as a Challenging Video Understanding Evaluation Framework

Santiago Castro, Ruoyao Wang, Pingxuan Huang +5

We propose fill-in-the-blanks as a video understanding evaluation framework and introduce FIBER -- a novel dataset consisting of 28,000 videos and descriptions in support of this e…