activity
20152026
most citedEqual But Not The Same: Understanding the Implicit Relationship Between Persuasive Images and Text

44 citations · 90 across the 34 of their papers we have counts for

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Showing 2024Show all

6 papers · 1 filter

cs.CV2024

CAP: Evaluation of Persuasive and Creative Image Generation

Aysan Aghazadeh, Adriana Kovashka

We address the task of advertisement image generation and introduce three evaluation metrics to assess Creativity, prompt Alignment, and Persuasiveness (CAP) in generated advertise…

cs.CV2024

Quantifying the Gaps Between Translation and Native Perception in Training for Multimodal, Multilingual Retrieval

Kyle Buettner, Adriana Kovashka

There is a scarcity of multilingual vision-language models that properly account for the perceptual differences that are reflected in image captions across languages and cultures.…

cs.CV2024

Enhancing Weakly-Supervised Object Detection on Static Images through (Hallucinated) Motion

Cagri Gungor, Adriana Kovashka

While motion has garnered attention in various tasks, its potential as a modality for weakly-supervised object detection (WSOD) in static images remains unexplored. Our study intro…

cs.CV2024

Integrating Audio Narrations to Strengthen Domain Generalization in Multimodal First-Person Action Recognition

Cagri Gungor, Adriana Kovashka

First-person activity recognition is rapidly growing due to the widespread use of wearable cameras but faces challenges from domain shifts across different environments, such as va…

cs.CV2024

Benchmarking VLMs' Reasoning About Persuasive Atypical Images

Sina Malakouti, Aysan Aghazadeh, Ashmit Khandelwal +1

Vision language models (VLMs) have shown strong zero-shot generalization across various tasks, especially when integrated with large language models (LLMs). However, their ability…

cs.CV2024

Incorporating Geo-Diverse Knowledge into Prompting for Increased Geographical Robustness in Object Recognition

Kyle Buettner, Sina Malakouti, Xiang Lorraine Li +1

Existing object recognition models have been shown to lack robustness in diverse geographical scenarios due to domain shifts in design and context. Class representations need to be…