Kostas Daniilidis

research

∙ 04/12/2022

Semantic keypoint-based pose estimation from single RGB frames

This paper presents an approach to estimating the continuous 6-DoF pose ...

Karl Schmeckpeper, et al. ∙

research

∙ 04/05/2022

SE(3)-Equivariant Attention Networks for Shape Reconstruction in Function Space

We propose the first SE(3)-equivariant coordinate-based network for lear...

Evangelos Chatzipantazis, et al. ∙

research

∙ 03/30/2022

CaDeX: Learning Canonical Deformation Coordinate Space for Dynamic Surface Representation via Neural Homeomorphism

While neural representations for static 3D shapes are widely studied, re...

Jiahui Lei, et al. ∙

research

∙ 03/10/2022

Cross-modal Map Learning for Vision and Language Navigation

We consider the problem of Vision-and-Language Navigation (VLN). The maj...

Georgios Georgakis, et al. ∙

research

∙ 02/24/2022

Uncertainty-driven Planner for Exploration and Navigation

We consider the problems of exploration and point-goal navigation in pre...

Georgios Georgakis, et al. ∙

research

∙ 11/16/2021

Learning Augmentation Distributions using Transformed Risk Minimization

Adapting to the structure of data distributions (such as symmetry and tr...

Evangelos Chatzipantazis, et al. ∙

research

∙ 10/18/2021

Discovering and Achieving Goals via World Models

How can artificial agents learn to solve many diverse tasks in complex v...

Russell Mendonca, et al. ∙

research

∙ 09/27/2021

Bridge Data: Boosting Generalization of Robotic Skills with Cross-Domain Datasets

Robot learning holds the promise of learning policies that generalize br...

Frederik Ebert, et al. ∙

research

∙ 09/06/2021

Single-Camera 3D Head Fitting for Mixed Reality Clinical Applications

We address the problem of estimating the shape of a person's head, defin...

Tejas Mane, et al. ∙

research

∙ 08/26/2021

Probabilistic Modeling for Human Mesh Recovery

This paper focuses on the problem of 3D human reconstruction from 2D evi...

Nikos Kolotouros, et al. ∙

research

∙ 06/29/2021

Learning to Map for Active Semantic Goal Navigation

We consider the problem of object goal navigation in unseen environments...

Georgios Georgakis, et al. ∙

research

∙ 06/24/2021

Model-Based Reinforcement Learning via Latent-Space Collocation

The ability to plan into the future while utilizing only raw high-dimens...

Oleh Rybkin, et al. ∙

research

∙ 05/19/2021

Birds of a Feather: Capturing Avian Shape Models from Images

Animals are diverse in shape, but building a deformable shape model for ...

Yufu Wang, et al. ∙

research

∙ 05/06/2021

Object-centric Video Prediction without Annotation

In order to interact with the world, agents must be able to predict the ...

Karl Schmeckpeper, et al. ∙

research

∙ 03/26/2021

Deformable Linear Object Prediction Using Locally Linear Latent Dynamics

We propose a framework for deformable linear object prediction. Predicti...

Wenbo Zhang, et al. ∙

research

∙ 12/08/2020

Learning Portrait Style Representations

Style analysis of artwork in computer vision predominantly focuses on ac...

Sadat Shaik, et al. ∙

research

∙ 12/05/2020

Joint Estimation of Image Representations and their Lie Invariants

Images encode both the state of the world and its content. The former is...

Christine Allen-Blanchette, et al. ∙

research

∙ 11/12/2020

Reinforcement Learning with Videos: Combining Offline Observations with Interaction

Reinforcement learning is a powerful framework for robots to acquire ski...

Karl Schmeckpeper, et al. ∙

research

∙ 08/13/2020

3D Bird Reconstruction: a Dataset, Model, and Shape Recovery from a Single View

Automated capture of animal pose is transforming how we study neuroscien...

Marc Badger, et al. ∙

research

∙ 07/06/2020

TLIO: Tight Learned Inertial Odometry

In this work we propose a tightly-coupled Extended Kalman Filter framewo...

Wenxin Liu, et al. ∙

research

∙ 06/23/2020

Simple and Effective VAE Training with Calibrated Decoders

Variational autoencoders (VAEs) provide an effective and simple method f...

Oleh Rybkin, et al. ∙

research

∙ 06/18/2020

Spin-Weighted Spherical CNNs

Learning equivariant representations is a promising way to reduce sample...

Carlos Esteves, et al. ∙

research

∙ 06/15/2020

Coherent Reconstruction of Multiple Humans from a Single Image

In this work, we address the problem of multi-person 3D pose estimation ...

Wen Jiang, et al. ∙

research

∙ 05/12/2020

Planning to Explore via Self-Supervised World Models

Reinforcement learning allows solving complex tasks, however, the learni...

Ramanan Sekar, et al. ∙

research

∙ 03/14/2020

Spike-FlowNet: Event-based Optical Flow Estimation with Energy-Efficient Hybrid Neural Networks

Event-based cameras display great potential for a variety of conditions ...

Chankyu Lee, et al. ∙

research

∙ 03/13/2020

Action for Better Prediction

Good prediction is necessary for autonomous robotics to make informed de...

Bernadette Bucher, et al. ∙

research

∙ 02/25/2020

Technical Report: Reactive Semantic Planning in Unexplored Semantic Environments Using Deep Perceptual Feedback

This paper presents a reactive planning system that enriches the topolog...

Vasileios Vasilopoulos, et al. ∙

research

∙ 02/20/2020

Reactive Navigation in Partially Familiar Planar Environments Using Semantic Perceptual Feedback

This paper solves the planar navigation problem by recourse to an online...

Vasileios Vasilopoulos, et al. ∙

research

∙ 12/30/2019

Learning Predictive Models From Observation and Interaction

Learning predictive models from interaction with the world allows an age...

Karl Schmeckpeper, et al. ∙

research

∙ 12/03/2019

EventGAN: Leveraging Large Scale Image Datasets for Event Cameras

Event cameras provide a number of benefits over traditional cameras, suc...

Alex Zihao Zhu, et al. ∙

research

∙ 10/24/2019

TexturePose: Supervising Human Mesh Estimation with Texture Consistency

This work addresses the problem of model-based human pose estimation. Re...

Georgios Pavlakos, et al. ∙

research

∙ 10/01/2019

TagSLAM: Robust SLAM with Fiducial Markers

TagSLAM provides a convenient, flexible, and robust way of performing Si...

Bernd Pfrommer, et al. ∙

research

∙ 09/27/2019

Learning to Reconstruct 3D Human Pose and Shape via Model-fitting in the Loop

Model-based human pose estimation is currently approached through two di...

Nikos Kolotouros, et al. ∙

research

∙ 05/08/2019

Convolutional Mesh Regression for Single-Image Human Shape Reconstruction

This paper addresses the problem of 3D human pose and shape estimation f...

Nikos Kolotouros, et al. ∙

research

∙ 04/17/2019

Event-based Vision: A Survey

Event cameras are bio-inspired sensors that work radically different fro...

Guillermo Gallego, et al. ∙

research

∙ 04/11/2019

KeyIn: Discovering Subgoal Structure with Keyframe-based Video Prediction

Real-world image sequences can often be naturally decomposed into a smal...

Karl Pertsch, et al. ∙

research

∙ 04/01/2019

Equivariant Multi-View Networks

Several approaches to 3D vision tasks process multiple views of the inpu...

Carlos Esteves, et al. ∙

research

∙ 02/18/2019

Motion Equivariant Networks for Event Cameras with the Temporal Normalization Transform

In this work, we propose a novel transformation for events from an event...

Alex Zihao Zhu, et al. ∙

research

∙ 01/07/2019

All Graphs Lead to Rome: Learning Geometric and Cycle-Consistent Representations with Graph Convolutional Networks

Image feature matching is a fundamental part of many geometric computer ...

Stephen Phillips, et al. ∙

research

∙ 12/29/2018

Monocular 3D Pose Recovery via Nonconvex Sparsity with Theoretical Analysis

For recovering 3D object poses from 2D images, a prevalent method is to ...

Jianqiao Wangni, et al. ∙

research

∙ 12/20/2018

Robustness Meets Deep Learning: An End-to-End Hybrid Pipeline for Unsupervised Learning of Egomotion

In this work, we propose a method that combines unsupervised deep learni...

Alex Zihao Zhu, et al. ∙

research

∙ 12/19/2018

Unsupervised Event-based Learning of Optical Flow, Depth, and Egomotion

In this work, we propose a novel framework for unsupervised learning for...

Alex Zihao Zhu, et al. ∙

research

∙ 12/06/2018

Cross-Domain 3D Equivariant Image Embeddings

Spherical convolutional networks have been introduced recently as tools ...

Carlos Esteves, et al. ∙

research

∙ 09/06/2018

Labeling Panoramas with Spherical Hourglass Networks

With the recent proliferation of consumer-grade 360 cameras, it is worth...

Carlos Esteves, et al. ∙

research

∙ 06/25/2018

Unsupervised Learning of Sensorimotor Affordances by Stochastic Future Prediction

Recently, much progress has been made building systems that can capture ...

Oleh Rybkin, et al. ∙

research

∙ 05/10/2018

Ordinal Depth Supervision for 3D Human Pose Estimation

Our ability to train end-to-end systems for 3D human pose estimation fro...

Georgios Pavlakos, et al. ∙

research

∙ 05/10/2018

Learning to Estimate 3D Human Pose and Shape from a Single Color Image

This work addresses the problem of estimating the full body 3D human pos...

Georgios Pavlakos, et al. ∙

research

∙ 04/17/2018

Human Motion Capture Using a Drone

Current motion capture (MoCap) systems generally require markers and mul...

Xiaowei Zhou, et al. ∙

research

∙ 03/26/2018

Predicting the Future with Transformational States

An intelligent observer looks at the world and sees not only what is, bu...

Andrew Jaegle, et al. ∙

research

∙ 03/24/2018

Realtime Time Synchronized Event-based Stereo

In this work, we propose a novel event based stereo method which address...

Alex Zihao Zhu, et al. ∙

Kostas Daniilidis

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