Search Results for author: Kiana Ehsani

Found 28 papers, 10 papers with code

PoliFormer: Scaling On-Policy RL with Transformers Results in Masterful Navigators

no code implementations28 Jun 2024 Kuo-Hao Zeng, Zichen Zhang, Kiana Ehsani, Rose Hendrix, Jordi Salvador, Alvaro Herrasti, Ross Girshick, Aniruddha Kembhavi, Luca Weihs

We present PoliFormer (Policy Transformer), an RGB-only indoor navigation agent trained end-to-end with reinforcement learning at scale that generalizes to the real-world without adaptation despite being trained purely in simulation.

Decoder Object +1

Manipulate-Anything: Automating Real-World Robots using Vision-Language Models

no code implementations27 Jun 2024 Jiafei Duan, Wentao Yuan, Wilbert Pumacay, Yi Ru Wang, Kiana Ehsani, Dieter Fox, Ranjay Krishna

Large-scale endeavors like RT-1 and widespread community efforts such as Open-X-Embodiment have contributed to growing the scale of robot demonstration data.

Diversity

Harmonic Mobile Manipulation

no code implementations11 Dec 2023 Ruihan Yang, Yejin Kim, Aniruddha Kembhavi, Xiaolong Wang, Kiana Ehsani

Recent advancements in robotics have enabled robots to navigate complex scenes or manipulate diverse objects independently.

Navigate

Structure from Action: Learning Interactions for Articulated Object 3D Structure Discovery

no code implementations19 Jul 2022 Neil Nie, Samir Yitzhak Gadre, Kiana Ehsani, Shuran Song

We introduce Structure from Action (SfA), a framework to discover 3D part geometry and joint parameters of unseen articulated objects via a sequence of inferred interactions.

Continuous Scene Representations for Embodied AI

no code implementations CVPR 2022 Samir Yitzhak Gadre, Kiana Ehsani, Shuran Song, Roozbeh Mottaghi

Our method captures feature relationships between objects, composes them into a graph structure on-the-fly, and situates an embodied agent within the representation.

Object Manipulation via Visual Target Localization

no code implementations15 Mar 2022 Kiana Ehsani, Ali Farhadi, Aniruddha Kembhavi, Roozbeh Mottaghi

Object manipulation is a critical skill required for Embodied AI agents interacting with the world around them.

Object object-detection +1

Towards Disturbance-Free Visual Mobile Manipulation

1 code implementation17 Dec 2021 Tianwei Ni, Kiana Ehsani, Luca Weihs, Jordi Salvador

In this paper, we study the problem of training agents to complete the task of visual mobile manipulation in the ManipulaTHOR environment while avoiding unnecessary collision (disturbance) with objects.

Collision Avoidance Knowledge Distillation +1

ManipulaTHOR: A Framework for Visual Object Manipulation

1 code implementation CVPR 2021 Kiana Ehsani, Winson Han, Alvaro Herrasti, Eli VanderBilt, Luca Weihs, Eric Kolve, Aniruddha Kembhavi, Roozbeh Mottaghi

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.

Object

Learning Visual Representation from Human Interactions

no code implementations ICLR 2021 Kiana Ehsani, Daniel Gordon, Thomas Hai Dang Nguyen, Roozbeh Mottaghi, Ali Farhadi

Learning effective representations of visual data that generalize to a variety of downstream tasks has been a long quest for computer vision.

Action Recognition Depth Estimation +2

Learning Flexible Visual Representations via Interactive Gameplay

no code implementations ICLR 2021 Luca Weihs, Aniruddha Kembhavi, Kiana Ehsani, Sarah M Pratt, Winson Han, Alvaro Herrasti, Eric Kolve, Dustin Schwenk, Roozbeh Mottaghi, Ali Farhadi

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.

Decision Making Representation Learning

Deconstructing the Structure of Sparse Neural Networks

no code implementations30 Nov 2020 Maxwell Van Gelder, Mitchell Wortsman, Kiana Ehsani

Although sparse neural networks have been studied extensively, the focus has been primarily on accuracy.

What Can You Learn from Your Muscles? Learning Visual Representation from Human Interactions

1 code implementation16 Oct 2020 Kiana Ehsani, Daniel Gordon, Thomas Nguyen, Roozbeh Mottaghi, Ali Farhadi

Learning effective representations of visual data that generalize to a variety of downstream tasks has been a long quest for computer vision.

Action Recognition Depth Estimation +2

Use the Force, Luke! Learning to Predict Physical Forces by Simulating Effects

3 code implementations CVPR 2020 Kiana Ehsani, Shubham Tulsiani, Saurabh Gupta, Ali Farhadi, Abhinav Gupta

Our quantitative and qualitative results show that (a) we can predict meaningful forces from videos whose effects lead to accurate imitation of the motions observed, (b) by jointly optimizing for contact point and force prediction, we can improve the performance on both tasks in comparison to independent training, and (c) we can learn a representation from this model that generalizes to novel objects using few shot examples.

Human-Object Interaction Detection

Watching the World Go By: Representation Learning from Unlabeled Videos

1 code implementation18 Mar 2020 Daniel Gordon, Kiana Ehsani, Dieter Fox, Ali Farhadi

Recent single image unsupervised representation learning techniques show remarkable success on a variety of tasks.

Data Augmentation Representation Learning

Learning Generalizable Visual Representations via Interactive Gameplay

no code implementations17 Dec 2019 Luca Weihs, Aniruddha Kembhavi, Kiana Ehsani, Sarah M Pratt, Winson Han, Alvaro Herrasti, Eric Kolve, Dustin Schwenk, Roozbeh Mottaghi, Ali Farhadi

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.

Decision Making Representation Learning

SeGAN: Segmenting and Generating the Invisible

1 code implementation CVPR 2018 Kiana Ehsani, Roozbeh Mottaghi, Ali Farhadi

Objects often occlude each other in scenes; Inferring their appearance beyond their visible parts plays an important role in scene understanding, depth estimation, object interaction and manipulation.

Depth Estimation Scene Understanding +1

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