5 papers
Object-centric Denoising Diffusion Models for Physical Reasoning
Moritz Lange, Raphael C. Engelhardt, Wolfgang Konen +2
Reasoning about the trajectories of multiple, interacting objects is integral to physical reasoning tasks in machine learning. This involves conditions imposed on the objects at di…
GRIM: Task-Oriented Grasping with Conditioning on Generative Examples
Shailesh, Alok Raj, Nayan Kumar +4
Task-Oriented Grasping (TOG) requires robots to select grasps that are functionally appropriate for a specified task - a challenge that demands an understanding of task semantics,…
SplatR : Experience Goal Visual Rearrangement with 3D Gaussian Splatting and Dense Feature Matching
Arjun P S, Andrew Melnik, Gora Chand Nandi
Experience Goal Visual Rearrangement task stands as a foundational challenge within Embodied AI, requiring an agent to construct a robust world model that accurately captures the g…
STEVE-Audio: Expanding the Goal Conditioning Modalities of Embodied Agents in Minecraft
Nicholas Lenzen, Amogh Raut, Andrew Melnik
Recently, the STEVE-1 approach has been introduced as a method for training generative agents to follow instructions in the form of latent CLIP embeddings. In this work, we present…
Object and Contact Point Tracking in Demonstrations Using 3D Gaussian Splatting
Michael Büttner, Jonathan Francis, Helge Rhodin +1
This paper introduces a method to enhance Interactive Imitation Learning (IIL) by extracting touch interaction points and tracking object movement from video demonstrations. The ap…