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Found 10 papers, 3 papers with code
A Joint Study of Phrase Grounding and Task Performance in Vision and Language Models
Key to tasks that require reasoning about natural language in visual contexts is grounding words and phrases to image regions.
Abstract Visual Reasoning with Tangram Shapes
We introduce KiloGram, a resource for studying abstract visual reasoning in humans and machines.
lilGym: Natural Language Visual Reasoning with Reinforcement Learning
We present lilGym, a new benchmark for language-conditioned reinforcement learning in visual environments.
Markup-to-Image Diffusion Models with Scheduled Sampling
These experiments each verify the effectiveness of the diffusion process and the use of scheduled sampling to fix generation issues.
Continual Learning for Grounded Instruction Generation by Observing Human Following Behavior
We study continual learning for natural language instruction generation, by observing human users' instruction execution.
OASIS: A Large-Scale Dataset for Single Image 3D in the Wild
Single-view 3D is the task of recovering 3D properties such as depth and surface normals from a single image.
What is Learned in Visually Grounded Neural Syntax Acquisition
Visual features are a promising signal for learning bootstrap textual models.
Representing Movie Characters in Dialogues
We introduce a new embedding model to represent movie characters and their interactions in a dialogue by encoding in the same representation the language used by these characters as well as information about the other participants in the dialogue.
To Learn or Not to Learn: Analyzing the Role of Learning for Navigation in Virtual Environments
In this paper we compare learning-based methods and classical methods for navigation in virtual environments.
Speaker Naming in Movies
We propose a new model for speaker naming in movies that leverages visual, textual, and acoustic modalities in an unified optimization framework.
