Search Results for author: Christopher Xie

Found 11 papers, 4 papers with code

RICE: Refining Instance Masks in Cluttered Environments with Graph Neural Networks

1 code implementation29 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.

FiG-NeRF: Figure-Ground Neural Radiance Fields for 3D Object Category Modelling

no code implementations17 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.


Amodal 3D Reconstruction for Robotic Manipulation via Stability and Connectivity

1 code implementation28 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.

3D Object Reconstruction 3D Reconstruction +1

Learning RGB-D Feature Embeddings for Unseen Object Instance Segmentation

1 code implementation30 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.

Clustering Metric Learning +4

The Best of Both Modes: Separately Leveraging RGB and Depth for Unseen Object Instance Segmentation

no code implementations30 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.

Object Segmentation +2

A Unified Framework for Long Range and Cold Start Forecasting of Seasonal Profiles in Time Series

no code implementations23 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.

Recommendation Systems Time Series +1

NonSTOP: A NonSTationary Online Prediction Method for Time Series

no code implementations8 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.

Time Series Time Series Analysis

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