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Found 11 papers, 5 papers with code
LocATe: End-to-end Localization of Actions in 3D with Transformers
An important component of this problem is 3D Temporal Action Localization (3D-TAL), which involves recognizing what actions a person is performing, and when.
How Much Coffee Was Consumed During EMNLP 2019? Fermi Problems: A New Reasoning Challenge for AI
FPs are commonly used in quizzes and interviews to bring out and evaluate the creative reasoning abilities of humans.
BABEL: Bodies, Action and Behavior with English Labels
To address this, we present BABEL, a large dataset with language labels describing the actions being performed in mocap sequences.
Ranked #1 on
Action Classification
on BABEL
Active Domain Adaptation via Clustering Uncertainty-weighted Embeddings
Generalizing deep neural networks to new target domains is critical to their real-world utility.
A Computational Model of Early Word Learning from the Infant's Point of View
Human infants have the remarkable ability to learn the associations between object names and visual objects from inherently ambiguous experiences.
Do Explanations make VQA Models more Predictable to a Human?
A rich line of research attempts to make deep neural networks more transparent by generating human-interpretable 'explanations' of their decision process, especially for interactive tasks like Visual Question Answering (VQA).
Evaluating Visual Conversational Agents via Cooperative Human-AI Games
This suggests a mismatch between benchmarking of AI in isolation and in the context of human-AI teams.
Punny Captions: Witty Wordplay in Image Descriptions
Wit is a form of rich interaction that is often grounded in a specific situation (e. g., a comment in response to an event).
It Takes Two to Tango: Towards Theory of AI's Mind
Surprisingly, we find that having access to the model's internal states - its confidence in its top-k predictions, explicit or implicit attention maps which highlight regions in the image (and words in the question) the model is looking at (and listening to) while answering a question about an image - do not help people better predict its behavior.
Sort Story: Sorting Jumbled Images and Captions into Stories
Temporal common sense has applications in AI tasks such as QA, multi-document summarization, and human-AI communication.
We Are Humor Beings: Understanding and Predicting Visual Humor
We collect two datasets of abstract scenes that facilitate the study of humor at both the scene-level and the object-level.
