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Found 6 papers, 5 papers with code
Analyzing Modular Approaches for Visual Question Decomposition
Modular neural networks without additional training have recently been shown to surpass end-to-end neural networks on challenging vision-language tasks.
What's in a Decade? Transforming Faces Through Time
How can one visually characterize people in a decade?
A-OKVQA: A Benchmark for Visual Question Answering using World Knowledge
In contrast to the existing knowledge-based VQA datasets, the questions generally cannot be answered by simply querying a knowledge base, and instead require some form of commonsense reasoning about the scene depicted in the image.
Simple but Effective: CLIP Embeddings for Embodied AI
Contrastive language image pretraining (CLIP) encoders have been shown to be beneficial for a range of visual tasks from classification and detection to captioning and image manipulation.
Who's Waldo? Linking People Across Text and Images
We present a task and benchmark dataset for person-centric visual grounding, the problem of linking between people named in a caption and people pictured in an image.
Ranked #1 on
Person-centric Visual Grounding
on Who’s Waldo
(using extra training data)
An Ethical Highlighter for People-Centric Dataset Creation
Important ethical concerns arising from computer vision datasets of people have been receiving significant attention, and a number of datasets have been withdrawn as a result.
