Pre-trained Text-to-Image Diffusion Models Are Versatile Representation Learners for Control

9 May 2024

Papers citing "Pre-trained Text-to-Image Diffusion Models Are Versatile Representation Learners for Control"

8 / 8 papers shown

Title
Synthetic Experience Replay Cong Lu Philip J. Ball Yee Whye Teh Jack Parker-Holder OffRL 84 65 0 12 Mar 2023
Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Models Jiarui Xu Sifei Liu Arash Vahdat Wonmin Byeon Xiaolong Wang Shalini De Mello VLM 209 318 0 08 Mar 2023
DALL-E-Bot: Introducing Web-Scale Diffusion Models to Robotics Ivan Kapelyukh Vitalis Vosylius Edward Johns LM&Ro DiffM 99 143 0 05 Oct 2022
LM-Nav: Robotic Navigation with Large Pre-Trained Models of Language, Vision, and Action Dhruv Shah B. Osinski Brian Ichter Sergey Levine LM&Ro 139 430 0 10 Jul 2022
ZSON: Zero-Shot Object-Goal Navigation using Multimodal Goal Embeddings Arjun Majumdar Gunjan Aggarwal Bhavika Devnani Judy Hoffman Dhruv Batra LM&Ro 147 148 0 24 Jun 2022
Planning with Diffusion for Flexible Behavior Synthesis Michael Janner Yilun Du J. Tenenbaum Sergey Levine DiffM 202 622 0 20 May 2022
Label-Efficient Semantic Segmentation with Diffusion Models Dmitry Baranchuk Ivan Rubachev A. Voynov Valentin Khrulkov Artem Babenko DiffM VLM 195 508 0 06 Dec 2021
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger Philipp Fischer Thomas Brox SSeg 3DV 229 74,467 0 18 May 2015