Thomas Funkhouser

research

∙ 05/09/2023

TidyBot: Personalized Robot Assistance with Large Language Models

For a robot to personalize physical assistance effectively, it must lear...

0 Jimmy Wu, et al. ∙

research

∙ 04/07/2023

Clutter Detection and Removal in 3D Scenes with View-Consistent Inpainting

Removing clutter from scenes is essential in many applications, ranging ...

0 Fangyin Wei, et al. ∙

research

∙ 03/06/2023

Nerflets: Local Radiance Fields for Efficient Structure-Aware 3D Scene Representation from 2D Supervision

We address efficient and structure-aware 3D scene representation from im...

0 Xiaoshuai Zhang, et al. ∙

research

∙ 02/09/2023

Polynomial Neural Fields for Subband Decomposition and Manipulation

Neural fields have emerged as a new paradigm for representing signals, t...

3 Guandao Yang, et al. ∙

research

∙ 11/28/2022

OpenScene: 3D Scene Understanding with Open Vocabularies

Traditional 3D scene understanding approaches rely on labeled 3D dataset...

0 Songyou Peng, et al. ∙

research

∙ 11/25/2022

Forecasting Actions and Characteristic 3D Poses

We propose to model longer-term future human behavior by jointly predict...

0 Christian Diller, et al. ∙

research

∙ 07/30/2022

MobileNeRF: Exploiting the Polygon Rasterization Pipeline for Efficient Neural Field Rendering on Mobile Architectures

Neural Radiance Fields (NeRFs) have demonstrated amazing ability to synt...

0 Zhiqin Chen, et al. ∙

research

∙ 05/09/2022

Panoptic Neural Fields: A Semantic Object-Aware Neural Scene Representation

We present Panoptic Neural Fields (PNF), an object-aware neural scene re...

32 Abhijit Kundu, et al. ∙

research

∙ 04/05/2022

Learning Pneumatic Non-Prehensile Manipulation with a Mobile Blower

We investigate pneumatic non-prehensile manipulation (i.e., blowing) as ...

0 Jimmy Wu, et al. ∙

research

∙ 12/14/2021

Revisiting 3D Object Detection From an Egocentric Perspective

3D object detection is a key module for safety-critical robotics applica...

0 Boyang Deng, et al. ∙

research

∙ 11/29/2021

Urban Radiance Fields

The goal of this work is to perform 3D reconstruction and novel view syn...

0 Konstantinos Rematas, et al. ∙

research

∙ 11/25/2021

Scene Representation Transformer: Geometry-Free Novel View Synthesis Through Set-Latent Scene Representations

A classical problem in computer vision is to infer a 3D scene representa...

0 Mehdi S. M. Sajjadi, et al. ∙

research

∙ 10/21/2021

Learning 3D Semantic Segmentation with only 2D Image Supervision

With the recent growth of urban mapping and autonomous driving efforts, ...

0 Kyle Genova, et al. ∙

research

∙ 09/12/2021

Multiresolution Deep Implicit Functions for 3D Shape Representation

We introduce Multiresolution Deep Implicit Functions (MDIF), a hierarchi...

8 Zhang Chen, et al. ∙

research

∙ 07/06/2021

Contrastive Multimodal Fusion with TupleInfoNCE

This paper proposes a method for representation learning of multimodal d...

7 Yunze Liu, et al. ∙

research

∙ 03/23/2021

Spatial Intention Maps for Multi-Agent Mobile Manipulation

The ability to communicate intention enables decentralized multi-agent r...

5 Jimmy Wu, et al. ∙

research

∙ 02/25/2021

IBRNet: Learning Multi-View Image-Based Rendering

We present a method that synthesizes novel views of complex scenes by in...

0 Qianqian Wang, et al. ∙

research

∙ 12/24/2020

P4Contrast: Contrastive Learning with Pairs of Point-Pixel Pairs for RGB-D Scene Understanding

Self-supervised representation learning is a critical problem in compute...

2 Yunze Liu, et al. ∙

research

∙ 12/15/2020

Object-Centric Neural Scene Rendering

We present a method for composing photorealistic scenes from captured im...

8 Michelle Guo, et al. ∙

research

∙ 12/08/2020

Robust Neural Routing Through Space Partitions for Camera Relocalization in Dynamic Indoor Environments

Localizing the camera in a known indoor environment is a key building bl...

4 Siyan Dong, et al. ∙

research

∙ 11/30/2020

Forecasting Characteristic 3D Poses of Human Actions

We propose the task of forecasting characteristic 3D poses: from a singl...

0 Christian Diller, et al. ∙

research

∙ 11/09/2020

Learning to Infer Semantic Parameters for 3D Shape Editing

Many applications in 3D shape design and augmentation require the abilit...

6 Fangyin Wei, et al. ∙

research

∙ 09/24/2020

Multi-Frame to Single-Frame: Knowledge Distillation for 3D Object Detection

A common dilemma in 3D object detection for autonomous driving is that h...

0 Yue Wang, et al. ∙

research

∙ 07/26/2020

Virtual Multi-view Fusion for 3D Semantic Segmentation

Semantic segmentation of 3D meshes is an important problem for 3D scene ...

2 Abhijit Kundu, et al. ∙

research

∙ 07/24/2020

An LSTM Approach to Temporal 3D Object Detection in LiDAR Point Clouds

Detecting objects in 3D LiDAR data is a core technology for autonomous d...

35 Rui Huang, et al. ∙

research

∙ 07/20/2020

Pillar-based Object Detection for Autonomous Driving

We present a simple and flexible object detection framework optimized fo...

10 Yue Wang, et al. ∙

research

∙ 07/16/2020

Complete Label: A Domain Adaptation Approach to Semantic Segmentation of LiDAR Point Clouds

We study an unsupervised domain adaptation problem for the semantic labe...

0 Li Yi, et al. ∙

research

∙ 04/20/2020

Spatial Action Maps for Mobile Manipulation

This paper proposes a new action representation for learning to perform ...

3 Jimmy Wu, et al. ∙

research

∙ 03/19/2020

Local Implicit Grid Representations for 3D Scenes

Shape priors learned from data are commonly used to reconstruct 3D objec...

44 Chiyu "Max" Jiang, et al. ∙

research

∙ 03/18/2020

Adversarial Texture Optimization from RGB-D Scans

Realistic color texture generation is an important step in RGB-D surface...

7 Jingwei Huang, et al. ∙

research

∙ 12/12/2019

Deep Structured Implicit Functions

The goal of this project is to learn a 3D shape representation that enab...

22 Kyle Genova, et al. ∙

research

∙ 12/12/2019

Local Deep Implicit Functions for 3D Shape

The goal of this project is to learn a 3D shape representation that enab...

0 Kyle Genova, et al. ∙

research

∙ 12/09/2019

Grasping in the Wild:Learning 6DoF Closed-Loop Grasping from Low-Cost Demonstrations

Intelligent manipulation benefits from the capacity to flexibly control ...

13 Shuran Song, et al. ∙

research

∙ 09/25/2019

Rescan: Inductive Instance Segmentation for Indoor RGBD Scans

In depth-sensing applications ranging from home robotics to AR/VR, it wi...

9 Maciej Halber, et al. ∙

research

∙ 06/18/2019

Neural Illumination: Lighting Prediction for Indoor Environments

This paper addresses the task of estimating the light arriving from all ...

3 Shuran Song, et al. ∙

research

∙ 04/12/2019

Learning Shape Templates with Structured Implicit Functions

Template 3D shapes are useful for many tasks in graphics and vision, inc...

16 Kyle Genova, et al. ∙

research

∙ 03/29/2019

FrameNet: Learning Local Canonical Frames of 3D Surfaces from a Single RGB Image

In this work, we introduce the novel problem of identifying dense canoni...

4 Jingwei Huang, et al. ∙

research

∙ 03/27/2019

TossingBot: Learning to Throw Arbitrary Objects with Residual Physics

We investigate whether a robot arm can learn to pick and throw arbitrary...

8 Andy Zeng, et al. ∙

research

∙ 11/30/2018

TextureNet: Consistent Local Parametrizations for Learning from High-Resolution Signals on Meshes

We introduce, TextureNet, a neural network architecture designed to extr...

0 Jingwei Huang, et al. ∙

research

∙ 08/04/2018

Structure-Aware Shape Synthesis

We propose a new procedure to guide training of a data-driven shape gene...

6 Elena Balashova, et al. ∙

research

∙ 07/16/2018

ActiveStereoNet: End-to-End Self-Supervised Learning for Active Stereo Systems

In this paper we present ActiveStereoNet, the first deep learning soluti...

4 Yinda Zhang, et al. ∙

research

∙ 03/27/2018

Learning Synergies between Pushing and Grasping with Self-supervised Deep Reinforcement Learning

Skilled robotic manipulation benefits from complex synergies between non...

0 Andy Zeng, et al. ∙

research

∙ 03/25/2018

Deep Depth Completion of a Single RGB-D Image

The goal of our work is to complete the depth channel of an RGB-D image....

0 Yinda Zhang, et al. ∙

research

∙ 03/22/2018

Text2Shape: Generating Shapes from Natural Language by Learning Joint Embeddings

We present a method for generating colored 3D shapes from natural langua...

4 Kevin Chen, et al. ∙

research

∙ 03/22/2018

PlaneMatch: Patch Coplanarity Prediction for Robust RGB-D Reconstruction

We introduce a novel RGB-D patch descriptor designed for detecting copla...

0 Yifei Shi, et al. ∙

research

∙ 12/12/2017

Im2Pano3D: Extrapolating 360 Structure and Semantics Beyond the Field of View

We present Im2Pano3D, a convolutional neural network that generates a de...

0 Shuran Song, et al. ∙

research

∙ 12/11/2017

MINOS: Multimodal Indoor Simulator for Navigation in Complex Environments

We present MINOS, a simulator designed to support the development of mul...

0 Manolis Savva, et al. ∙

research

∙ 10/17/2017

Large-Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55

We introduce a large-scale 3D shape understanding benchmark using data a...

0 Li Yi, et al. ∙

research

∙ 10/03/2017

Robotic Pick-and-Place of Novel Objects in Clutter with Multi-Affordance Grasping and Cross-Domain Image Matching

This paper presents a robotic pick-and-place system that is capable of g...

0 Andy Zeng, et al. ∙

research

∙ 09/18/2017

Matterport3D: Learning from RGB-D Data in Indoor Environments

Access to large, diverse RGB-D datasets is critical for training RGB-D s...

0 Angel Chang, et al. ∙

Thomas Funkhouser

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