Kostas Daniilidis

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Ryerson University ∙ University of Pennsylvania

Ruth Yalom Stone Professor of Computer and Information Science at University of Pennsylvania, Scientific Advisor - Co-Founder at COSY - Cognitive Operational Systems, Inc., Director at GRASP Laboratory, University of Pennsylvania from 2008-2013, Co-Founder at kapou.gr from 2008-2012

Featured Co-authors

Sergey Levine
249 publications
Pieter Abbeel
170 publications
Ji Liu
96 publications
Chelsea Finn
92 publications
Dahua Lin
88 publications
Davide Scaramuzza
72 publications
Kaushik Roy
63 publications
Vijay Kumar
57 publications
Michael J. Black
54 publications
Ke Sun
52 publications
George J. Pappas
51 publications

Deformable Linear Object Prediction Using Locally Linear Latent Dynamics

We propose a framework for deformable linear object prediction. Predicti...
03/26/2021 ∙ by Wenbo Zhang, et al. ∙ 0 ∙ share

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Learning Portrait Style Representations

Style analysis of artwork in computer vision predominantly focuses on ac...
12/08/2020 ∙ by Sadat Shaik, et al. ∙ 5 ∙ share

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Joint Estimation of Image Representations and their Lie Invariants

Images encode both the state of the world and its content. The former is...
12/05/2020 ∙ by Christine Allen-Blanchette, et al. ∙ 0 ∙ share

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Reinforcement Learning with Videos: Combining Offline Observations with Interaction

Reinforcement learning is a powerful framework for robots to acquire ski...
11/12/2020 ∙ by Karl Schmeckpeper, et al. ∙ 15 ∙ share

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

Automated capture of animal pose is transforming how we study neuroscien...
08/13/2020 ∙ by Marc Badger, et al. ∙ 3 ∙ share

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TLIO: Tight Learned Inertial Odometry

In this work we propose a tightly-coupled Extended Kalman Filter framewo...
07/06/2020 ∙ by Wenxin Liu, et al. ∙ 0 ∙ share

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Simple and Effective VAE Training with Calibrated Decoders

Variational autoencoders (VAEs) provide an effective and simple method f...
06/23/2020 ∙ by Oleh Rybkin, et al. ∙ 22 ∙ share

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Spin-Weighted Spherical CNNs

Learning equivariant representations is a promising way to reduce sample...
06/18/2020 ∙ by Carlos Esteves, et al. ∙ 11 ∙ share

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Coherent Reconstruction of Multiple Humans from a Single Image

In this work, we address the problem of multi-person 3D pose estimation ...
06/15/2020 ∙ by Wen Jiang, et al. ∙ 4 ∙ share

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Planning to Explore via Self-Supervised World Models

Reinforcement learning allows solving complex tasks, however, the learni...
05/12/2020 ∙ by Ramanan Sekar, et al. ∙ 2 ∙ share

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

Event-based cameras display great potential for a variety of conditions ...
03/14/2020 ∙ by Chankyu Lee, et al. ∙ 18 ∙ share

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Action for Better Prediction

Good prediction is necessary for autonomous robotics to make informed de...
03/13/2020 ∙ by Bernadette Bucher, et al. ∙ 6 ∙ share

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

This paper presents a reactive planning system that enriches the topolog...
02/25/2020 ∙ by Vasileios Vasilopoulos, et al. ∙ 0 ∙ share

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Reactive Navigation in Partially Familiar Planar Environments Using Semantic Perceptual Feedback

This paper solves the planar navigation problem by recourse to an online...
02/20/2020 ∙ by Vasileios Vasilopoulos, et al. ∙ 0 ∙ share

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Learning Predictive Models From Observation and Interaction

Learning predictive models from interaction with the world allows an age...
12/30/2019 ∙ by Karl Schmeckpeper, et al. ∙ 12 ∙ share

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EventGAN: Leveraging Large Scale Image Datasets for Event Cameras

Event cameras provide a number of benefits over traditional cameras, suc...
12/03/2019 ∙ by Alex Zihao Zhu, et al. ∙ 16 ∙ share

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TexturePose: Supervising Human Mesh Estimation with Texture Consistency

This work addresses the problem of model-based human pose estimation. Re...
10/24/2019 ∙ by Georgios Pavlakos, et al. ∙ 15 ∙ share

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TagSLAM: Robust SLAM with Fiducial Markers

TagSLAM provides a convenient, flexible, and robust way of performing Si...
10/01/2019 ∙ by Bernd Pfrommer, et al. ∙ 20 ∙ share

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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...
09/27/2019 ∙ by Nikos Kolotouros, et al. ∙ 5 ∙ share

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Convolutional Mesh Regression for Single-Image Human Shape Reconstruction

This paper addresses the problem of 3D human pose and shape estimation f...
05/08/2019 ∙ by Nikos Kolotouros, et al. ∙ 8 ∙ share

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Event-based Vision: A Survey

Event cameras are bio-inspired sensors that work radically different fro...
04/17/2019 ∙ by Guillermo Gallego, et al. ∙ 18 ∙ share

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KeyIn: Discovering Subgoal Structure with Keyframe-based Video Prediction

Real-world image sequences can often be naturally decomposed into a smal...
04/11/2019 ∙ by Karl Pertsch, et al. ∙ 4 ∙ share

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Equivariant Multi-View Networks

Several approaches to 3D vision tasks process multiple views of the inpu...
04/01/2019 ∙ by Carlos Esteves, et al. ∙ 14 ∙ share

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Motion Equivariant Networks for Event Cameras with the Temporal Normalization Transform

In this work, we propose a novel transformation for events from an event...
02/18/2019 ∙ by Alex Zihao Zhu, et al. ∙ 0 ∙ share

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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 ...
01/07/2019 ∙ by Stephen Phillips, et al. ∙ 8 ∙ share

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Monocular 3D Pose Recovery via Nonconvex Sparsity with Theoretical Analysis

For recovering 3D object poses from 2D images, a prevalent method is to ...
12/29/2018 ∙ by Jianqiao Wangni, et al. ∙ 24 ∙ share

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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...
12/20/2018 ∙ by Alex Zihao Zhu, et al. ∙ 6 ∙ share

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

In this work, we propose a novel framework for unsupervised learning for...
12/19/2018 ∙ by Alex Zihao Zhu, et al. ∙ 0 ∙ share

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Cross-Domain 3D Equivariant Image Embeddings

Spherical convolutional networks have been introduced recently as tools ...
12/06/2018 ∙ by Carlos Esteves, et al. ∙ 14 ∙ share

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Labeling Panoramas with Spherical Hourglass Networks

With the recent proliferation of consumer-grade 360 cameras, it is worth...
09/06/2018 ∙ by Carlos Esteves, et al. ∙ 6 ∙ share

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Unsupervised Learning of Sensorimotor Affordances by Stochastic Future Prediction

Recently, much progress has been made building systems that can capture ...
06/25/2018 ∙ by Oleh Rybkin, et al. ∙ 0 ∙ share

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Ordinal Depth Supervision for 3D Human Pose Estimation

Our ability to train end-to-end systems for 3D human pose estimation fro...
05/10/2018 ∙ by Georgios Pavlakos, et al. ∙ 0 ∙ share

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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...
05/10/2018 ∙ by Georgios Pavlakos, et al. ∙ 0 ∙ share

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Human Motion Capture Using a Drone

Current motion capture (MoCap) systems generally require markers and mul...
04/17/2018 ∙ by Xiaowei Zhou, et al. ∙ 0 ∙ share

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Predicting the Future with Transformational States

An intelligent observer looks at the world and sees not only what is, bu...
03/26/2018 ∙ by Andrew Jaegle, et al. ∙ 0 ∙ share

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Realtime Time Synchronized Event-based Stereo

In this work, we propose a novel event based stereo method which address...
03/24/2018 ∙ by Alex Zihao Zhu, et al. ∙ 0 ∙ share

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EV-FlowNet: Self-Supervised Optical Flow Estimation for Event-based Cameras

Event-based cameras have shown great promise in a variety of situations ...
02/19/2018 ∙ by Alex Zihao Zhu, et al. ∙ 0 ∙ share

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The Multi Vehicle Stereo Event Camera Dataset: An Event Camera Dataset for 3D Perception

Event based cameras are a new passive sensing modality with a number of ...
01/30/2018 ∙ by Alex Zihao Zhu, et al. ∙ 0 ∙ share

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Fast, Autonomous Flight in GPS-Denied and Cluttered Environments

One of the most challenging tasks for a flying robot is to autonomously ...
12/06/2017 ∙ by Kartik Mohta, et al. ∙ 0 ∙ share

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Multi-Image Semantic Matching by Mining Consistent Features

This work proposes a multi-image matching method to estimate semantic co...
11/21/2017 ∙ by Qianqian Wang, et al. ∙ 0 ∙ share

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3D object classification and retrieval with Spherical CNNs

3D object classification and retrieval presents many challenges that are...
11/17/2017 ∙ by Carlos Esteves, et al. ∙ 0 ∙ share

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Polar Transformer Networks

Convolutional neural networks (CNNs) are inherently equivariant to trans...
09/06/2017 ∙ by Carlos Esteves, et al. ∙ 0 ∙ share

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6-DoF Object Pose from Semantic Keypoints

This paper presents a novel approach to estimating the continuous six de...
03/14/2017 ∙ by Georgios Pavlakos, et al. ∙ 0 ∙ share

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MonoCap: Monocular Human Motion Capture using a CNN Coupled with a Geometric Prior

Recovering 3D full-body human pose is a challenging problem with many ap...
01/09/2017 ∙ by Xiaowei Zhou, et al. ∙ 0 ∙ share

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Unsupervised learning of image motion by recomposing sequences

We propose a new method for learning a representation of image motion in...
12/01/2016 ∙ by Andrew Jaegle, et al. ∙ 0 ∙ share

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Coarse-to-Fine Volumetric Prediction for Single-Image 3D Human Pose

This paper addresses the challenge of 3D human pose estimation from a si...
11/23/2016 ∙ by Georgios Pavlakos, et al. ∙ 0 ∙ share

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Fast, Robust, Continuous Monocular Egomotion Computation

We propose robust methods for estimating camera egomotion in noisy, real...
02/16/2016 ∙ by Andrew Jaegle, et al. ∙ 0 ∙ share

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Sparseness Meets Deepness: 3D Human Pose Estimation from Monocular Video

This paper addresses the challenge of 3D full-body human pose estimation...
11/30/2015 ∙ by Xiaowei Zhou, et al. ∙ 0 ∙ share

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Sparse Representation for 3D Shape Estimation: A Convex Relaxation Approach

We investigate the problem of estimating the 3D shape of an object defin...
09/14/2015 ∙ by Xiaowei Zhou, et al. ∙ 0 ∙ share

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Pose and Shape Estimation with Discriminatively Learned Parts

We introduce a new approach for estimating the 3D pose and the 3D shape ...
02/01/2015 ∙ by Menglong Zhu, et al. ∙ 0 ∙ share

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