Search Results for author: Ravi Garg

Found 16 papers, 5 papers with code

Feasibility Study on Intra-Grid Location Estimation Using Power ENF Signals

no code implementations3 May 2021 Ravi Garg, Adi Hajj-Ahmad, Min Wu

In this study, we demonstrate that it is possible to pinpoint the location-of-recording to a certain geographical resolution using power signal recordings containing strong ENF traces.

DF-VO: What Should Be Learnt for Visual Odometry?

2 code implementations1 Mar 2021 Huangying Zhan, Chamara Saroj Weerasekera, Jia-Wang Bian, Ravi Garg, Ian Reid

More surprisingly, they show that the well-trained networks enable scale-consistent predictions over long videos, while the accuracy is still inferior to traditional methods because of ignoring geometric information.

Monocular Visual Odometry Optical Flow Estimation

Improved Visual Localization via Graph Smoothing

no code implementations7 Nov 2019 Carlos Lassance, Yasir Latif, Ravi Garg, Vincent Gripon, Ian Reid

One solution to this problem is to learn a deep neural network to infer the pose of a query image after learning on a dataset of images with known poses.

Image Retrieval Visual Localization

Non-Parametric Priors For Generative Adversarial Networks

no code implementations16 May 2019 Rajhans Singh, Pavan Turaga, Suren Jayasuriya, Ravi Garg, Martin W. Braun

The advent of generative adversarial networks (GAN) has enabled new capabilities in synthesis, interpolation, and data augmentation heretofore considered very challenging.

Data Augmentation Image Generation

Self-supervised Learning for Single View Depth and Surface Normal Estimation

no code implementations1 Mar 2019 Huangying Zhan, Chamara Saroj Weerasekera, Ravi Garg, Ian Reid

In this work we present a self-supervised learning framework to simultaneously train two Convolutional Neural Networks (CNNs) to predict depth and surface normals from a single image.

Depth Prediction Monocular Depth Estimation +2

Just-in-Time Reconstruction: Inpainting Sparse Maps using Single View Depth Predictors as Priors

no code implementations11 May 2018 Chamara Saroj Weerasekera, Thanuja Dharmasiri, Ravi Garg, Tom Drummond, Ian Reid

Crucially, we obtain the confidence weights that parameterize the CRF model in a data-dependent manner via Convolutional Neural Networks (CNNs) which are trained to model the conditional depth error distributions given each source of input depth map and the associated RGB image.

Depth Estimation Depth Prediction

Unsupervised Learning of Monocular Depth Estimation and Visual Odometry with Deep Feature Reconstruction

1 code implementation CVPR 2018 Huangying Zhan, Ravi Garg, Chamara Saroj Weerasekera, Kejie Li, Harsh Agarwal, Ian Reid

Despite learning based methods showing promising results in single view depth estimation and visual odometry, most existing approaches treat the tasks in a supervised manner.

Depth And Camera Motion Depth Prediction +2

Learning Deeply Supervised Good Features to Match for Dense Monocular Reconstruction

no code implementations16 Nov 2017 Chamara Saroj Weerasekera, Ravi Garg, Yasir Latif, Ian Reid

Visual SLAM (Simultaneous Localization and Mapping) methods typically rely on handcrafted visual features or raw RGB values for establishing correspondences between images.

Depth Estimation Simultaneous Localization and Mapping

Addressing Challenging Place Recognition Tasks using Generative Adversarial Networks

1 code implementation26 Sep 2017 Yasir Latif, Ravi Garg, Michael Milford, Ian Reid

In the process, meaningful feature spaces are learned for each domain, the distances in which can be used for the task of place recognition.


Adaptive Low-Rank Kernel Subspace Clustering

1 code implementation17 Jul 2017 Pan Ji, Ian Reid, Ravi Garg, Hongdong Li, Mathieu Salzmann

In this paper, we present a kernel subspace clustering method that can handle non-linear models.

Image Clustering Motion Segmentation

Unsupervised CNN for Single View Depth Estimation: Geometry to the Rescue

2 code implementations16 Mar 2016 Ravi Garg, Vijay Kumar BG, Gustavo Carneiro, Ian Reid

In this work we propose a unsupervised framework to learn a deep convolutional neural network for single view depth predic- tion, without requiring a pre-training stage or annotated ground truth depths.

Depth Estimation

Non-linear Dimensionality Regularizer for Solving Inverse Problems

no code implementations16 Mar 2016 Ravi Garg, Anders Eriksson, Ian Reid

Additionally, we evaluate our method on the challenging problem of Non-Rigid Structure from Motion and our approach delivers promising results on CMU mocap dataset despite the presence of significant occlusions and noise.

Dense Variational Reconstruction of Non-rigid Surfaces from Monocular Video

no code implementations CVPR 2013 Ravi Garg, Anastasios Roussos, Lourdes Agapito

This paper offers the first variational approach to the problem of dense 3D reconstruction of non-rigid surfaces from a monocular video sequence.

3D Reconstruction

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