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Found 14 papers, 7 papers with code
AI2-THOR: An Interactive 3D Environment for Visual AI
We introduce The House Of inteRactions (THOR), a framework for visual AI research, available at http://ai2thor. allenai. org.
RoboTHOR: An Open Simulation-to-Real Embodied AI Platform
We argue that interactive and embodied visual AI has reached a stage of development similar to visual recognition prior to the advent of these ecosystems.
CORA: Benchmarks, Baselines, and Metrics as a Platform for Continual Reinforcement Learning Agents
In this work, we present CORA, a platform for Continual Reinforcement Learning Agents that provides benchmarks, baselines, and metrics in a single code package.
ManipulaTHOR: A Framework for Visual Object Manipulation
Object manipulation is an established research domain within the robotics community and poses several challenges including manipulator motion, grasping and long-horizon planning, particularly when dealing with oft-overlooked practical setups involving visually rich and complex scenes, manipulation using mobile agents (as opposed to tabletop manipulation), and generalization to unseen environments and objects.
A Diagram Is Worth A Dozen Images
We define syntactic parsing of diagrams as learning to infer DPGs for diagrams and study semantic interpretation and reasoning of diagrams in the context of diagram question answering.
Target-driven Visual Navigation in Indoor Scenes using Deep Reinforcement Learning
To address the second issue, we propose AI2-THOR framework, which provides an environment with high-quality 3D scenes and physics engine.
Iconary: A Pictionary-Based Game for Testing Multimodal Communication with Drawings and Text
We investigate these challenges in the context of Iconary, a collaborative game of drawing and guessing based on Pictionary, that poses a novel challenge for the research community.
Visual Semantic Planning using Deep Successor Representations
A crucial capability of real-world intelligent agents is their ability to plan a sequence of actions to achieve their goals in the visual world.
Two Body Problem: Collaborative Visual Task Completion
Collaboration is a necessary skill to perform tasks that are beyond one agent's capabilities.
Learning Generalizable Visual Representations via Interactive Gameplay
A growing body of research suggests that embodied gameplay, prevalent not just in human cultures but across a variety of animal species including turtles and ravens, is critical in developing the neural flexibility for creative problem solving, decision making, and socialization.
A Cordial Sync: Going Beyond Marginal Policies for Multi-Agent Embodied Tasks
Autonomous agents must learn to collaborate.
Learning Flexible Visual Representations via Interactive Gameplay
A growing body of research suggests that embodied gameplay, prevalent not just in human cultures but across a variety of animal species including turtles and ravens, is critical in developing the neural flexibility for creative problem solving, decision making and socialization.
Webly Supervised Concept Expansion for General Purpose Vision Models
This work presents an effective and inexpensive alternative: learn skills from supervised datasets, learn concepts from web image search, and leverage a key characteristic of GPVs: the ability to transfer visual knowledge across skills.
Ranked #2 on
Visual Question Answering (VQA)
on GRIT
ProcTHOR: Large-Scale Embodied AI Using Procedural Generation
Massive datasets and high-capacity models have driven many recent advancements in computer vision and natural language understanding.
