Search Results for author:
Found 10 papers, 5 papers with code
Scaling Text-Rich Image Understanding via Code-Guided Synthetic Multimodal Data Generation
Reasoning about images with rich text, such as charts and documents, is a critical application of vision-language models (VLMs).
From an Image to a Scene: Learning to Imagine the World from a Million 360 Videos
We train our diffusion-based model, Odin, on 360-1M.
Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models
Today's most advanced vision-language models (VLMs) remain proprietary.
Objaverse: A Universe of Annotated 3D Objects
Massive data corpora like WebText, Wikipedia, Conceptual Captions, WebImageText, and LAION have propelled recent dramatic progress in AI.
Phone2Proc: Bringing Robust Robots Into Our Chaotic World
Training embodied agents in simulation has become mainstream for the embodied AI community.
Retrospectives on the Embodied AI Workshop
We present a retrospective on the state of Embodied AI research.
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.
Visual Room Rearrangement
We particularly focus on the task of Room Rearrangement: an agent begins by exploring a room and recording objects' initial configurations.
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.
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.
