no code implementations • ICML 2020 • Ramanan Sekar, Oleh Rybkin, Kostas Daniilidis, Pieter Abbeel, Danijar Hafner, Deepak Pathak
To solve complex tasks, intelligent agents first need to explore their environments.
no code implementations • 27 May 2024 • Jiahui Lei, Yijia Weng, Adam Harley, Leonidas Guibas, Kostas Daniilidis
We introduce 4D Motion Scaffolds (MoSca), a neural information processing system designed to reconstruct and synthesize novel views of dynamic scenes from monocular videos captured casually in the wild.
1 code implementation • 27 Mar 2024 • Bo Wu, Bruce D. Lee, Kostas Daniilidis, Bernadette Bucher, Nikolai Matni
Large-scale robotic policies trained on data from diverse tasks and robotic platforms hold great promise for enabling general-purpose robots; however, reliable generalization to new environment conditions remains a major challenge.
no code implementations • 26 Mar 2024 • Yunzhou Song, Jiahui Lei, ZiYun Wang, Lingjie Liu, Kostas Daniilidis
We propose a novel test-time optimization approach for efficiently and robustly tracking any pixel at any time in a video.
1 code implementation • 26 Mar 2024 • Yufu Wang, ZiYun Wang, Lingjie Liu, Kostas Daniilidis
We propose TRAM, a two-stage method to reconstruct a human's global trajectory and motion from in-the-wild videos.
Ranked #1 on 3D Human Pose Estimation on EMDB
no code implementations • 30 Nov 2023 • Agelos Kratimenos, Jiahui Lei, Kostas Daniilidis
We argue that the per-point motions of a dynamic scene can be decomposed into a small set of explicit or learned trajectories.
no code implementations • 30 Nov 2023 • ZiYun Wang, Friedhelm Hamann, Kenneth Chaney, Wen Jiang, Guillermo Gallego, Kostas Daniilidis
We present ContinuityCam, a novel approach to generate a continuous video from a single static RGB image, using an event camera.
no code implementations • 30 Nov 2023 • ZiYun Wang, Jinyuan Guo, Kostas Daniilidis
Event cameras are a novel type of biologically inspired vision sensor known for their high temporal resolution, high dynamic range, and low power consumption.
1 code implementation • 29 Nov 2023 • Wen Jiang, Boshu Lei, Kostas Daniilidis
This study addresses the challenging problem of active view selection and uncertainty quantification within the domain of Radiance Fields.
no code implementations • 27 Nov 2023 • Jiahui Lei, Yufu Wang, Georgios Pavlakos, Lingjie Liu, Kostas Daniilidis
We introduce Gaussian Articulated Template Model GART, an explicit, efficient, and expressive representation for non-rigid articulated subject capturing and rendering from monocular videos.
1 code implementation • 3 Oct 2023 • Anish Bhattacharya, Ratnesh Madaan, Fernando Cladera, Sai Vemprala, Rogerio Bonatti, Kostas Daniilidis, Ashish Kapoor, Vijay Kumar, Nikolai Matni, Jayesh K. Gupta
We present EvDNeRF, a pipeline for generating event data and training an event-based dynamic NeRF, for the purpose of faithfully reconstructing eventstreams on scenes with rigid and non-rigid deformations that may be too fast to capture with a standard camera.
no code implementations • ICCV 2023 • Yufu Wang, Kostas Daniilidis
We present Recurrent Fitting (ReFit), a neural network architecture for single-image, parametric 3D human reconstruction.
no code implementations • 7 Jun 2023 • Diego Patiño, Siddharth Mayya, Juan Calderon, Kostas Daniilidis, David Saldaña
This problem is made even more complex when a team of aerial robots is trying to achieve coordinated motion in turbulent wind conditions.
no code implementations • 25 May 2023 • Jiahui Lei, Congyue Deng, Bokui Shen, Leonidas Guibas, Kostas Daniilidis
We propose Neural 3D Articulation Prior (NAP), the first 3D deep generative model to synthesize 3D articulated object models.
no code implementations • 14 Apr 2023 • ZiYun Wang, Fernando Cladera Ojeda, Anthony Bisulco, Daewon Lee, Camillo J. Taylor, Kostas Daniilidis, M. Ani Hsieh, Daniel D. Lee, Volkan Isler
Event-based sensors have recently drawn increasing interest in robotic perception due to their lower latency, higher dynamic range, and lower bandwidth requirements compared to standard CMOS-based imagers.
1 code implementation • 11 Apr 2023 • ZiYun Wang, Kenneth Chaney, Kostas Daniilidis
3D reconstruction from multiple views is a successful computer vision field with multiple deployments in applications.
no code implementations • CVPR 2023 • Jiahui Lei, Congyue Deng, Karl Schmeckpeper, Leonidas Guibas, Kostas Daniilidis
First, we introduce equivariant shape representations to this problem to eliminate the complexity induced by the variation in object configuration.
no code implementations • 30 Dec 2022 • Yinshuang Xu, Jiahui Lei, Kostas Daniilidis
We model the ray space, the domain of the light field, as a homogeneous space of $SE(3)$ and introduce the $SE(3)$-equivariant convolution in ray space.
1 code implementation • ICCV 2023 • Yiming Wang, Qin Han, Marc Habermann, Kostas Daniilidis, Christian Theobalt, Lingjie Liu
Recent methods for neural surface representation and rendering, for example NeuS, have demonstrated the remarkably high-quality reconstruction of static scenes.
no code implementations • 6 Dec 2022 • Wen Jiang, Kostas Daniilidis
Due to the redundancy of local feature volumes, this tensor completion problem can be further reduced to estimating the canonical factors of the feature volume.
no code implementations • 1 Dec 2022 • Shiting Xiao, Yufu Wang, Ammon Perkes, Bernd Pfrommer, Marc Schmidt, Kostas Daniilidis, Marc Badger
The ability to capture detailed interactions among individuals in a social group is foundational to our study of animal behavior and neuroscience.
no code implementations • 16 Jun 2022 • Yinshuang Xu, Jiahui Lei, Edgar Dobriban, Kostas Daniilidis
We present a unified derivation of kernels via the Fourier domain by leveraging the sparsity of Fourier coefficients of the lifted feature fields.
1 code implementation • 12 Apr 2022 • Karl Schmeckpeper, Philip R. Osteen, Yufu Wang, Georgios Pavlakos, Kenneth Chaney, Wyatt Jordan, Xiaowei Zhou, Konstantinos G. Derpanis, Kostas Daniilidis
Empirically, we show that our approach can accurately recover the 6-DoF object pose for both instance- and class-based scenarios even against a cluttered background.
no code implementations • 5 Apr 2022 • Evangelos Chatzipantazis, Stefanos Pertigkiozoglou, Edgar Dobriban, Kostas Daniilidis
In contrast to previous shape reconstruction methods that align the input to a regular grid, we operate directly on the irregular point cloud.
1 code implementation • CVPR 2022 • Jiahui Lei, Kostas Daniilidis
While neural representations for static 3D shapes are widely studied, representations for deformable surfaces are limited to be template-dependent or lack efficiency.
1 code implementation • CVPR 2022 • Georgios Georgakis, Karl Schmeckpeper, Karan Wanchoo, Soham Dan, Eleni Miltsakaki, Dan Roth, Kostas Daniilidis
We consider the problem of Vision-and-Language Navigation (VLN).
1 code implementation • 24 Feb 2022 • Georgios Georgakis, Bernadette Bucher, Anton Arapin, Karl Schmeckpeper, Nikolai Matni, Kostas Daniilidis
We consider the problems of exploration and point-goal navigation in previously unseen environments, where the spatial complexity of indoor scenes and partial observability constitute these tasks challenging.
no code implementations • 16 Nov 2021 • Evangelos Chatzipantazis, Stefanos Pertigkiozoglou, Kostas Daniilidis, Edgar Dobriban
We propose a new \emph{Transformed Risk Minimization} (TRM) framework as an extension of classical risk minimization.
2 code implementations • NeurIPS 2021 • Russell Mendonca, Oleh Rybkin, Kostas Daniilidis, Danijar Hafner, Deepak Pathak
How can artificial agents learn to solve many diverse tasks in complex visual environments in the absence of any supervision?
no code implementations • 29 Sep 2021 • Diego Patino, Carlos Esteves, Kostas Daniilidis
In this paper we propose a deep learning method for unsupervised 3D implicit shape reconstruction from point clouds.
2 code implementations • 27 Sep 2021 • Frederik Ebert, Yanlai Yang, Karl Schmeckpeper, Bernadette Bucher, Georgios Georgakis, Kostas Daniilidis, Chelsea Finn, Sergey Levine
Robot learning holds the promise of learning policies that generalize broadly.
no code implementations • 6 Sep 2021 • Tejas Mane, Aylar Bayramova, Kostas Daniilidis, Philippos Mordohai, Elena Bernardis
We address the problem of estimating the shape of a person's head, defined as the geometry of the complete head surface, from a video taken with a single moving camera, and determining the alignment of the fitted 3D head for all video frames, irrespective of the person's pose.
1 code implementation • ICCV 2021 • Nikos Kolotouros, Georgios Pavlakos, Dinesh Jayaraman, Kostas Daniilidis
This paper focuses on the problem of 3D human reconstruction from 2D evidence.
Ranked #70 on 3D Human Pose Estimation on Human3.6M (PA-MPJPE metric)
2 code implementations • ICLR 2022 • Georgios Georgakis, Bernadette Bucher, Karl Schmeckpeper, Siddharth Singh, Kostas Daniilidis
We consider the problem of object goal navigation in unseen environments.
1 code implementation • 24 Jun 2021 • Oleh Rybkin, Chuning Zhu, Anusha Nagabandi, Kostas Daniilidis, Igor Mordatch, Sergey Levine
The resulting latent collocation method (LatCo) optimizes trajectories of latent states, which improves over previously proposed shooting methods for visual model-based RL on tasks with sparse rewards and long-term goals.
Model-based Reinforcement Learning reinforcement-learning +1
no code implementations • ICML Workshop URL 2021 • Russell Mendonca, Oleh Rybkin, Kostas Daniilidis, Danijar Hafner, Deepak Pathak
How can an artificial agent learn to solve a wide range of tasks in a complex visual environment in the absence of external supervision?
1 code implementation • CVPR 2021 • Yufu Wang, Nikos Kolotouros, Kostas Daniilidis, Marc Badger
We learn models of multiple species from the CUB dataset, and contribute new species-specific and multi-species shape models that are useful for downstream reconstruction tasks.
1 code implementation • 6 May 2021 • Karl Schmeckpeper, Georgios Georgakis, Kostas Daniilidis
Object-centric video prediction offers a solution to these problems by taking advantage of the simple prior that the world is made of objects and by providing a more natural interface for control.
1 code implementation • 26 Mar 2021 • Wenbo Zhang, Karl Schmeckpeper, Pratik Chaudhari, Kostas Daniilidis
We empirically demonstrate that our approach can predict the rope state accurately up to ten steps into the future and that our algorithm can find the optimal action given an initial state and a goal state.
1 code implementation • 8 Dec 2020 • Sadat Shaik, Bernadette Bucher, Nephele Agrafiotis, Stephen Phillips, Kostas Daniilidis, William Schmenner
We study style representations learned by neural network architectures incorporating these higher level characteristics.
no code implementations • 5 Dec 2020 • Christine Allen-Blanchette, Kostas Daniilidis
In both approaches, the underlying dynamics of the image sequence are modelled explicitly to disentangle them from the image representations.
1 code implementation • 12 Nov 2020 • Karl Schmeckpeper, Oleh Rybkin, Kostas Daniilidis, Sergey Levine, Chelsea Finn
In this paper, we consider the question: can we perform reinforcement learning directly on experience collected by humans?
1 code implementation • ECCV 2020 • Marc Badger, Yufu Wang, Adarsh Modh, Ammon Perkes, Nikos Kolotouros, Bernd G. Pfrommer, Marc F. Schmidt, Kostas Daniilidis
Automated capture of animal pose is transforming how we study neuroscience and social behavior.
no code implementations • 6 Jul 2020 • Wenxin Liu, David Caruso, Eddy Ilg, Jing Dong, Anastasios I. Mourikis, Kostas Daniilidis, Vijay Kumar, Jakob Engel
We show that our network, trained with pedestrian data from a headset, can produce statistically consistent measurement and uncertainty to be used as the update step in the filter, and the tightly-coupled system outperforms velocity integration approaches in position estimates, and AHRS attitude filter in orientation estimates.
1 code implementation • 23 Jun 2020 • Oleh Rybkin, Kostas Daniilidis, Sergey Levine
We perform the first comprehensive comparative analysis of calibrated decoder and provide recommendations for simple and effective VAE training.
2 code implementations • NeurIPS 2020 • Carlos Esteves, Ameesh Makadia, Kostas Daniilidis
In this paper, we present a new type of spherical CNN that allows anisotropic filters in an efficient way, without ever leaving the spherical domain.
Ranked #20 on Semantic Segmentation on Stanford2D3D Panoramic
1 code implementation • CVPR 2020 • Wen Jiang, Nikos Kolotouros, Georgios Pavlakos, Xiaowei Zhou, Kostas Daniilidis
Our goal is to train a single network that learns to avoid these problems and generate a coherent 3D reconstruction of all the humans in the scene.
Ranked #2 on 3D Human Reconstruction on AGORA
4 code implementations • 12 May 2020 • Ramanan Sekar, Oleh Rybkin, Kostas Daniilidis, Pieter Abbeel, Danijar Hafner, Deepak Pathak
Reinforcement learning allows solving complex tasks, however, the learning tends to be task-specific and the sample efficiency remains a challenge.
1 code implementation • ECCV 2020 • Chankyu Lee, Adarsh Kumar Kosta, Alex Zihao Zhu, Kenneth Chaney, Kostas Daniilidis, Kaushik Roy
Spiking Neural Networks (SNNs) serve as ideal paradigms to handle event camera outputs, but deep SNNs suffer in terms of performance due to the spike vanishing phenomenon.
1 code implementation • 13 Mar 2020 • Bernadette Bucher, Karl Schmeckpeper, Nikolai Matni, Kostas Daniilidis
Model-based curiosity combines active learning approaches to optimal sampling with the information gain based incentives for exploration presented in the curiosity literature.
2 code implementations • 20 Feb 2020 • Vasileios Vasilopoulos, Georgios Pavlakos, Karl Schmeckpeper, Kostas Daniilidis, Daniel E. Koditschek
This paper solves the planar navigation problem by recourse to an online reactive scheme that exploits recent advances in SLAM and visual object recognition to recast prior geometric knowledge in terms of an offline catalogue of familiar objects.
Robotics
no code implementations • ECCV 2020 • Karl Schmeckpeper, Annie Xie, Oleh Rybkin, Stephen Tian, Kostas Daniilidis, Sergey Levine, Chelsea Finn
Learning predictive models from interaction with the world allows an agent, such as a robot, to learn about how the world works, and then use this learned model to plan coordinated sequences of actions to bring about desired outcomes.
1 code implementation • 3 Dec 2019 • Alex Zihao Zhu, ZiYun Wang, Kaung Khant, Kostas Daniilidis
Event cameras provide a number of benefits over traditional cameras, such as the ability to track incredibly fast motions, high dynamic range, and low power consumption.
1 code implementation • ICCV 2019 • Georgios Pavlakos, Nikos Kolotouros, Kostas Daniilidis
Assuming that the texture of the person does not change dramatically between frames, we can apply a novel texture consistency loss, which enforces that each point in the texture map has the same texture value across all frames.
Ranked #27 on Weakly-supervised 3D Human Pose Estimation on Human3.6M
no code implementations • 1 Oct 2019 • Bernd Pfrommer, Kostas Daniilidis
TagSLAM provides a convenient, flexible, and robust way of performing Simultaneous Localization and Mapping (SLAM) with AprilTag fiducial markers.
1 code implementation • ICCV 2019 • Nikos Kolotouros, Georgios Pavlakos, Michael J. Black, Kostas Daniilidis
Our approach is self-improving by nature, since better network estimates can lead the optimization to better solutions, while more accurate optimization fits provide better supervision for the network.
no code implementations • 25 Sep 2019 • Stephen Phillips, Kostas Daniilidis
In geometric computer vision applications, multi-image feature matching gives more accurate and robust solutions compared to simple two-image matching.
no code implementations • 25 Sep 2019 • Karl Pertsch, Oleh Rybkin, Jingyun Yang, Konstantinos G. Derpanis, Kostas Daniilidis, Joseph J. Lim, Andrew Jaegle
To flexibly and efficiently reason about temporal sequences, abstract representations that compactly represent the important information in the sequence are needed.
2 code implementations • CVPR 2019 • Nikos Kolotouros, Georgios Pavlakos, Kostas Daniilidis
Image-based features are attached to the mesh vertices and the Graph-CNN is responsible to process them on the mesh structure, while the regression target for each vertex is its 3D location.
Ranked #34 on Monocular 3D Human Pose Estimation on Human3.6M
3D Hand Pose Estimation 3D human pose and shape estimation +2
1 code implementation • 17 Apr 2019 • Guillermo Gallego, Tobi Delbruck, Garrick Orchard, Chiara Bartolozzi, Brian Taba, Andrea Censi, Stefan Leutenegger, Andrew Davison, Joerg Conradt, Kostas Daniilidis, Davide Scaramuzza
Event cameras offer attractive properties compared to traditional cameras: high temporal resolution (in the order of microseconds), very high dynamic range (140 dB vs. 60 dB), low power consumption, and high pixel bandwidth (on the order of kHz) resulting in reduced motion blur.
no code implementations • L4DC 2020 • Karl Pertsch, Oleh Rybkin, Jingyun Yang, Shenghao Zhou, Konstantinos G. Derpanis, Kostas Daniilidis, Joseph Lim, Andrew Jaegle
We propose a model that learns to discover these important events and the times when they occur and uses them to represent the full sequence.
1 code implementation • ICCV 2019 • Carlos Esteves, Yinshuang Xu, Christine Allen-Blanchette, Kostas Daniilidis
Several popular approaches to 3D vision tasks process multiple views of the input independently with deep neural networks pre-trained on natural images, achieving view permutation invariance through a single round of pooling over all views.
no code implementations • 18 Feb 2019 • Alex Zihao Zhu, ZiYun Wang, Kostas Daniilidis
In this work, we propose a novel transformation for events from an event camera that is equivariant to optical flow under convolutions in the 3-D spatiotemporal domain.
1 code implementation • 7 Jan 2019 • Stephen Phillips, Kostas Daniilidis
Image feature matching is a fundamental part of many geometric computer vision applications, and using multiple images can improve performance.
no code implementations • 29 Dec 2018 • Jianqiao Wangni, Dahua Lin, Ji Liu, Kostas Daniilidis, Jianbo Shi
For recovering 3D object poses from 2D images, a prevalent method is to pre-train an over-complete dictionary $\mathcal D=\{B_i\}_i^D$ of 3D basis poses.
no code implementations • 20 Dec 2018 • Alex Zihao Zhu, Wenxin Liu, ZiYun Wang, Vijay Kumar, Kostas Daniilidis
In this work, we propose a method that combines unsupervised deep learning predictions for optical flow and monocular disparity with a model based optimization procedure for instantaneous camera pose.
2 code implementations • CVPR 2019 • Alex Zihao Zhu, Liangzhe Yuan, Kenneth Chaney, Kostas Daniilidis
In this work, we propose a novel framework for unsupervised learning for event cameras that learns motion information from only the event stream.
1 code implementation • 6 Dec 2018 • Carlos Esteves, Avneesh Sud, Zhengyi Luo, Kostas Daniilidis, Ameesh Makadia
This embedding encodes images with 3D shape properties and is equivariant to 3D rotations of the observed object.
no code implementations • 6 Sep 2018 • Carlos Esteves, Kostas Daniilidis, Ameesh Makadia
With the recent proliferation of consumer-grade 360{\deg} cameras, it is worth revisiting visual perception challenges with spherical cameras given the potential benefit of their global field of view.
no code implementations • ICLR 2019 • Oleh Rybkin, Karl Pertsch, Konstantinos G. Derpanis, Kostas Daniilidis, Andrew Jaegle
We introduce a loss term that encourages the network to capture the composability of visual sequences and show that it leads to representations that disentangle the structure of actions.
1 code implementation • CVPR 2018 • Georgios Pavlakos, Xiaowei Zhou, Kostas Daniilidis
This information can be acquired by human annotators for a wide range of images and poses.
Ranked #1 on Monocular 3D Human Pose Estimation on Human3.6M (Use Video Sequence metric)
no code implementations • CVPR 2018 • Georgios Pavlakos, Luyang Zhu, Xiaowei Zhou, Kostas Daniilidis
The proposed approach outperforms previous baselines on this task and offers an attractive solution for direct prediction of 3D shape from a single color image.
Ranked #120 on 3D Human Pose Estimation on Human3.6M (PA-MPJPE metric)
1 code implementation • 17 Apr 2018 • Xiaowei Zhou, Sikang Liu, Georgios Pavlakos, Vijay Kumar, Kostas Daniilidis
Current motion capture (MoCap) systems generally require markers and multiple calibrated cameras, which can be used only in constrained environments.
no code implementations • 26 Mar 2018 • Andrew Jaegle, Oleh Rybkin, Konstantinos G. Derpanis, Kostas Daniilidis
We couple this latent state with a recurrent neural network (RNN) core that predicts future frames by transforming past states into future states by applying the accumulated state transformation with a learned operator.
no code implementations • ECCV 2018 • Alex Zihao Zhu, Yibo Chen, Kostas Daniilidis
In this work, we propose a novel event based stereo method which addresses the problem of motion blur for a moving event camera.
2 code implementations • 19 Feb 2018 • Alex Zihao Zhu, Liangzhe Yuan, Kenneth Chaney, Kostas Daniilidis
Event-based cameras have shown great promise in a variety of situations where frame based cameras suffer, such as high speed motions and high dynamic range scenes.
no code implementations • 30 Jan 2018 • Alex Zihao Zhu, Dinesh Thakur, Tolga Ozaslan, Bernd Pfrommer, Vijay Kumar, Kostas Daniilidis
Event based cameras are a new passive sensing modality with a number of benefits over traditional cameras, including extremely low latency, asynchronous data acquisition, high dynamic range and very low power consumption.
Robotics
no code implementations • 6 Dec 2017 • Kartik Mohta, Michael Watterson, Yash Mulgaonkar, Sikang Liu, Chao Qu, Anurag Makineni, Kelsey Saulnier, Ke Sun, Alex Zhu, Jeffrey Delmerico, Konstantinos Karydis, Nikolay Atanasov, Giuseppe Loianno, Davide Scaramuzza, Kostas Daniilidis, Camillo Jose Taylor, Vijay Kumar
One of the most challenging tasks for a flying robot is to autonomously navigate between target locations quickly and reliably while avoiding obstacles in its path, and with little to no a-priori knowledge of the operating environment.
Robotics
2 code implementations • CVPR 2018 • Qianqian Wang, Xiaowei Zhou, Kostas Daniilidis
This work proposes a multi-image matching method to estimate semantic correspondences across multiple images.
3 code implementations • ECCV 2018 • Carlos Esteves, Christine Allen-Blanchette, Ameesh Makadia, Kostas Daniilidis
We address the problem of 3D rotation equivariance in convolutional neural networks.
no code implementations • ICCV 2017 • Roberto Tron, Xiaowei Zhou, Carlos Esteves, Kostas Daniilidis
We consider the problem of finding consistent matches across multiple images.
1 code implementation • ICLR 2018 • Carlos Esteves, Christine Allen-Blanchette, Xiaowei Zhou, Kostas Daniilidis
The result is a network invariant to translation and equivariant to both rotation and scale.
no code implementations • CVPR 2017 • Alex Zihao Zhu, Nikolay Atanasov, Kostas Daniilidis
An Extended Kalman Filter with a structureless measurement model then fuses the feature tracks with the output of the IMU.
no code implementations • CVPR 2017 • Georgios Pavlakos, Xiaowei Zhou, Konstantinos G. Derpanis, Kostas Daniilidis
In this paper, we present a geometry-driven approach to automatically collect annotations for human pose prediction tasks.
Ranked #28 on Weakly-supervised 3D Human Pose Estimation on Human3.6M
1 code implementation • 14 Mar 2017 • Georgios Pavlakos, Xiaowei Zhou, Aaron Chan, Konstantinos G. Derpanis, Kostas Daniilidis
This paper presents a novel approach to estimating the continuous six degree of freedom (6-DoF) pose (3D translation and rotation) of an object from a single RGB image.
Ranked #1 on Keypoint Detection on Pascal3D+
1 code implementation • 9 Jan 2017 • Xiaowei Zhou, Menglong Zhu, Georgios Pavlakos, Spyridon Leonardos, Kostantinos G. Derpanis, Kostas Daniilidis
Recovering 3D full-body human pose is a challenging problem with many applications.
no code implementations • ICLR 2018 • Andrew Jaegle, Stephen Phillips, Daphne Ippolito, Kostas Daniilidis
Our results demonstrate that this representation is useful for learning motion in the general setting where explicit labels are difficult to obtain.
3 code implementations • CVPR 2017 • Georgios Pavlakos, Xiaowei Zhou, Konstantinos G. Derpanis, Kostas Daniilidis
This paper addresses the challenge of 3D human pose estimation from a single color image.
Ranked #16 on 3D Human Pose Estimation on HumanEva-I
1 code implementation • 16 Feb 2016 • Andrew Jaegle, Stephen Phillips, Kostas Daniilidis
We propose robust methods for estimating camera egomotion in noisy, real-world monocular image sequences in the general case of unknown observer rotation and translation with two views and a small baseline.
no code implementations • ICCV 2015 • Menglong Zhu, Xiaowei Zhou, Kostas Daniilidis
We introduce a new approach for estimating a fine grained 3D shape and continuous pose of an object from a single image.
1 code implementation • CVPR 2016 • Xiaowei Zhou, Menglong Zhu, Spyridon Leonardos, Kosta Derpanis, Kostas Daniilidis
Here, two cases are considered: (i) the image locations of the human joints are provided and (ii) the image locations of joints are unknown.
Ranked #38 on Monocular 3D Human Pose Estimation on Human3.6M
no code implementations • 14 Sep 2015 • Xiaowei Zhou, Menglong Zhu, Spyridon Leonardos, Kostas Daniilidis
We investigate the problem of estimating the 3D shape of an object defined by a set of 3D landmarks, given their 2D correspondences in a single image.
Ranked #127 on 3D Human Pose Estimation on Human3.6M (PA-MPJPE metric)
no code implementations • CVPR 2015 • Spyridon Leonardos, Roberto Tron, Kostas Daniilidis
In this work, we investigate a new parametrization of the trifocal tensor for calibrated cameras with non-colinear pinholes obtained from a quotient Riemannian manifold.
1 code implementation • ICCV 2015 • Xiaowei Zhou, Menglong Zhu, Kostas Daniilidis
In this paper we propose a global optimization-based approach to jointly matching a set of images.
no code implementations • 1 Feb 2015 • Menglong Zhu, Xiaowei Zhou, Kostas Daniilidis
We introduce a new approach for estimating the 3D pose and the 3D shape of an object from a single image.
no code implementations • CVPR 2015 • Xiaowei Zhou, Spyridon Leonardos, Xiaoyan Hu, Kostas Daniilidis
We investigate the problem of estimating the 3D shape of an object, given a set of 2D landmarks in a single image.
no code implementations • CVPR 2014 • Roberto Tron, Kostas Daniilidis
The essential matrix, which encodes the epipolar constraint between points in two projective views, is a cornerstone of modern computer vision.
no code implementations • CVPR 2014 • Mayank Bansal, Kostas Daniilidis
We propose a purely geometric correspondence-free approach to urban geo-localization using 3D point-ray features extracted from the Digital Elevation Map of an urban environment.
no code implementations • 24 May 2014 • Mayank Bansal, Kostas Daniilidis
In this paper, we address the problem of finding correspondences in the absence of unary or pairwise constraints as it emerges in problems where unary appearance similarity like SIFT matches is not available.
no code implementations • 1 Apr 2014 • Menglong Zhu, Nikolay Atanasov, George J. Pappas, Kostas Daniilidis
This paper presents an active approach for part-based object detection, which optimizes the order of part filter evaluations and the time at which to stop and make a prediction.
no code implementations • 20 Sep 2013 • Nikolay Atanasov, Bharath Sankaran, Jerome Le Ny, George J. Pappas, Kostas Daniilidis
One of the central problems in computer vision is the detection of semantically important objects and the estimation of their pose.
no code implementations • CVPR 2013 • Mayank Bansal, Kostas Daniilidis
We address the problem of matching images with disparate appearance arising from factors like dramatic illumination (day vs. night), age (historic vs. new) and rendering style differences.
no code implementations • NeurIPS 2009 • Roy Anati, Kostas Daniilidis
We present a system which constructs a topological map of an environment given a sequence of images.