no code implementations • 19 Mar 2024 • Armen Avetisyan, Christopher Xie, Henry Howard-Jenkins, Tsun-Yi Yang, Samir Aroudj, Suvam Patra, Fuyang Zhang, Duncan Frost, Luke Holland, Campbell Orme, Jakob Engel, Edward Miller, Richard Newcombe, Vasileios Balntas
We introduce SceneScript, a method that directly produces full scene models as a sequence of structured language commands using an autoregressive, token-based approach.
1 code implementation • 29 Jun 2021 • Christopher Xie, Arsalan Mousavian, Yu Xiang, Dieter Fox
We postulate that a network architecture that encodes relations between objects at a high-level can be beneficial.
no code implementations • 17 Apr 2021 • Christopher Xie, Keunhong Park, Ricardo Martin-Brualla, Matthew Brown
We investigate the use of Neural Radiance Fields (NeRF) to learn high quality 3D object category models from collections of input images.
1 code implementation • 28 Sep 2020 • William Agnew, Christopher Xie, Aaron Walsman, Octavian Murad, Caelen Wang, Pedro Domingos, Siddhartha Srinivasa
By using these priors over the physical properties of objects, our system improves reconstruction quality not just by standard visual metrics, but also performance of model-based control on a variety of robotics manipulation tasks in challenging, cluttered environments.
1 code implementation • 30 Jul 2020 • Yu Xiang, Christopher Xie, Arsalan Mousavian, Dieter Fox
In this work, we propose a new method for unseen object instance segmentation by learning RGB-D feature embeddings from synthetic data.
1 code implementation • 16 Jul 2020 • Christopher Xie, Yu Xiang, Arsalan Mousavian, Dieter Fox
We also show that our method can segment unseen objects for robot grasping.
no code implementations • 30 Jul 2019 • Christopher Xie, Yu Xiang, Arsalan Mousavian, Dieter Fox
We show that our method, trained on this dataset, can produce sharp and accurate masks, outperforming state-of-the-art methods on unseen object instance segmentation.
no code implementations • CVPR 2019 • Christopher Xie, Yu Xiang, Zaid Harchaoui, Dieter Fox
We consider the problem of providing dense segmentation masks for object discovery in videos.
no code implementations • 23 Oct 2017 • Christopher Xie, Alex Tank, Alec Greaves-Tunnell, Emily Fox
Providing long-range forecasts is a fundamental challenge in time series modeling, which is only compounded by the challenge of having to form such forecasts when a time series has never previously been observed.
no code implementations • 8 Nov 2016 • Christopher Xie, Avleen Bijral, Juan Lavista Ferres
Moreover, since these transformations are usually unknown, we employ the learning with experts setting to develop a fully online method (NonSTOP-NonSTationary Online Prediction) for predicting nonstationary time series.
no code implementations • 23 Sep 2015 • Christopher Xie, Sachin Patil, Teodor Moldovan, Sergey Levine, Pieter Abbeel
In this paper, we present a robotic model-based reinforcement learning method that combines ideas from model identification and model predictive control.
Model-based Reinforcement Learning Model Predictive Control +2