Search Results for author: Marc Pollefeys

Found 145 papers, 56 papers with code

Calibration-free Structure-from-Motion with Calibrated Radial Trifocal Tensors

no code implementations ECCV 2020 Viktor Larsson, Nicolas Zobernig, Kasim Taskin, Marc Pollefeys

In this paper we consider the problem of Structure-from-Motion from images with unknown intrinsic calibration.

Handcrafted Outlier Detection Revisited

1 code implementation ECCV 2020 Luca Cavalli, Viktor Larsson, Martin Ralf Oswald, Torsten Sattler, Marc Pollefeys

As a result, outlier detection is a fundamental problem in computer vision and a wide range of approaches, from simple checks based on descriptor similarity to geometric verification, have been proposed over the last decades.

Computer Vision Outlier Detection +1

Context-Aware Sequence Alignment using 4D Skeletal Augmentation

no code implementations CVPR 2022 Taein Kwon, Bugra Tekin, Siyu Tang, Marc Pollefeys

Temporal alignment of fine-grained human actions in videos is important for numerous applications in computer vision, robotics, and mixed reality.

Computer Vision Hand Pose Estimation +2

Spatial Computing and Intuitive Interaction: Bringing Mixed Reality and Robotics Together

no code implementations3 Feb 2022 Jeffrey Delmerico, Roi Poranne, Federica Bogo, Helen Oleynikova, Eric Vollenweider, Stelian Coros, Juan Nieto, Marc Pollefeys

Spatial computing -- the ability of devices to be aware of their surroundings and to represent this digitally -- offers novel capabilities in human-robot interaction.

Mixed Reality

Learning To Find Good Models in RANSAC

no code implementations CVPR 2022 Daniel Barath, Luca Cavalli, Marc Pollefeys

We propose the Model Quality Network, MQ-Net in short, for predicting the quality, e. g. the pose error of essential matrices, of models generated inside RANSAC.

Pose Estimation

Camera Pose Estimation Using Implicit Distortion Models

no code implementations CVPR 2022 Linfei Pan, Marc Pollefeys, Viktor Larsson

Low-dimensional parametric models are the de-facto standard in computer vision for intrinsic camera calibration.

Camera Calibration Computer Vision +2

NICE-SLAM: Neural Implicit Scalable Encoding for SLAM

1 code implementation CVPR 2022 Zihan Zhu, Songyou Peng, Viktor Larsson, Weiwei Xu, Hujun Bao, Zhaopeng Cui, Martin R. Oswald, Marc Pollefeys

Neural implicit representations have recently shown encouraging results in various domains, including promising progress in simultaneous localization and mapping (SLAM).

Simultaneous Localization and Mapping

LatentHuman: Shape-and-Pose Disentangled Latent Representation for Human Bodies

no code implementations30 Nov 2021 Sandro Lombardi, Bangbang Yang, Tianxing Fan, Hujun Bao, Guofeng Zhang, Marc Pollefeys, Zhaopeng Cui

In this work, we propose a novel neural implicit representation for the human body, which is fully differentiable and optimizable with disentangled shape and pose latent spaces.

3D Reconstruction Computer Vision +2

Learning to Align Sequential Actions in the Wild

no code implementations CVPR 2022 Weizhe Liu, Bugra Tekin, Huseyin Coskun, Vibhav Vineet, Pascal Fua, Marc Pollefeys

To this end, we propose an approach to enforce temporal priors on the optimal transport matrix, which leverages temporal consistency, while allowing for variations in the order of actions.

Representation Learning

Non-local Recurrent Regularization Networks for Multi-view Stereo

no code implementations13 Oct 2021 Qingshan Xu, Martin R. Oswald, Wenbing Tao, Marc Pollefeys, Zhaopeng Cui

However, existing recurrent methods only model the local dependencies in the depth domain, which greatly limits the capability of capturing the global scene context along the depth dimension.

Depth Estimation

Reconstructing and grounding narrated instructional videos in 3D

no code implementations9 Sep 2021 Dimitri Zhukov, Ignacio Rocco, Ivan Laptev, Josef Sivic, Johannes L. Schönberger, Bugra Tekin, Marc Pollefeys

Contrary to the standard scenario of instance-level 3D reconstruction, where identical objects or scenes are present in all views, objects in different instructional videos may have large appearance variations given varying conditions and versions of the same product.

3D Reconstruction

Learning Motion Priors for 4D Human Body Capture in 3D Scenes

no code implementations ICCV 2021 Siwei Zhang, Yan Zhang, Federica Bogo, Marc Pollefeys, Siyu Tang

To prove the effectiveness of the proposed motion priors, we combine them into a novel pipeline for 4D human body capture in 3D scenes.

Shape from Blur: Recovering Textured 3D Shape and Motion of Fast Moving Objects

1 code implementation NeurIPS 2021 Denys Rozumnyi, Martin R. Oswald, Vittorio Ferrari, Marc Pollefeys

We address the novel task of jointly reconstructing the 3D shape, texture, and motion of an object from a single motion-blurred image.

Deblurring Super-Resolution +1

Shape As Points: A Differentiable Poisson Solver

1 code implementation NeurIPS 2021 Songyou Peng, Chiyu "Max" Jiang, Yiyi Liao, Michael Niemeyer, Marc Pollefeys, Andreas Geiger

However, the implicit nature of neural implicit representations results in slow inference time and requires careful initialization.

3D Reconstruction Surface Reconstruction

Towards Efficient Graph Convolutional Networks for Point Cloud Handling

no code implementations ICCV 2021 Yawei Li, He Chen, Zhaopeng Cui, Radu Timofte, Marc Pollefeys, Gregory Chirikjian, Luc van Gool

In this paper, we aim at improving the computational efficiency of graph convolutional networks (GCNs) for learning on point clouds.

Back to the Feature: Learning Robust Camera Localization from Pixels to Pose

1 code implementation CVPR 2021 Paul-Edouard Sarlin, Ajaykumar Unagar, Måns Larsson, Hugo Germain, Carl Toft, Viktor Larsson, Marc Pollefeys, Vincent Lepetit, Lars Hammarstrand, Fredrik Kahl, Torsten Sattler

In this paper, we go Back to the Feature: we argue that deep networks should focus on learning robust and invariant visual features, while the geometric estimation should be left to principled algorithms.

Camera Localization Metric Learning +1

Holistic 3D Scene Understanding from a Single Image with Implicit Representation

1 code implementation CVPR 2021 Cheng Zhang, Zhaopeng Cui, yinda zhang, Bing Zeng, Marc Pollefeys, Shuaicheng Liu

We not only propose an image-based local structured implicit network to improve the object shape estimation, but also refine the 3D object pose and scene layout via a novel implicit scene graph neural network that exploits the implicit local object features.

 Ranked #1 on Room Layout Estimation on SUN RGB-D (using extra training data)

Monocular 3D Object Detection object-detection +2

Localizing Unsynchronized Sensors with Unknown Sources

1 code implementation6 Feb 2021 Dalia El Badawy, Viktor Larsson, Marc Pollefeys, Ivan Dokmanić

We look at the general case where neither the emission times of the sources nor the reference time frames of the receivers are known.

Orthographic-Perspective Epipolar Geometry

no code implementations ICCV 2021 Viktor Larsson, Marc Pollefeys, Magnus Oskarsson

In this paper we consider the epipolar geometry between orthographic and perspective cameras.

Camera Calibration

The Card Shuffling Hypotheses: Building a Time and Memory Efficient Graph Convolutional Network

no code implementations1 Jan 2021 Yawei Li, He Chen, Zhaopeng Cui, Radu Timofte, Marc Pollefeys, Gregory Chirikjian, Luc van Gool

State-of-the-art GCNs adopt $K$-nearest neighbor (KNN) searches for local feature aggregation and feature extraction operations from layer to layer.

3D Classification Point Cloud Classification +1

DeepSurfels: Learning Online Appearance Fusion

1 code implementation CVPR 2021 Marko Mihajlovic, Silvan Weder, Marc Pollefeys, Martin R. Oswald

We present DeepSurfels, a novel hybrid scene representation for geometry and appearance information.

CodeVIO: Visual-Inertial Odometry with Learned Optimizable Dense Depth

no code implementations18 Dec 2020 Xingxing Zuo, Nathaniel Merrill, Wei Li, Yong liu, Marc Pollefeys, Guoquan Huang

In this work, we present a lightweight, tightly-coupled deep depth network and visual-inertial odometry (VIO) system, which can provide accurate state estimates and dense depth maps of the immediate surroundings.

Depth Estimation Pose Estimation

FMODetect: Robust Detection of Fast Moving Objects

1 code implementation ICCV 2021 Denys Rozumnyi, Jiri Matas, Filip Sroubek, Marc Pollefeys, Martin R. Oswald

Compared to other methods, such as deblatting, the inference is of several orders of magnitude faster and allows applications such as real-time fast moving object detection and retrieval in large video collections.

Deblurring Image Matting +2

Sat2Vid: Street-view Panoramic Video Synthesis from a Single Satellite Image

no code implementations ICCV 2021 Zuoyue Li, Zhenqiang Li, Zhaopeng Cui, Rongjun Qin, Marc Pollefeys, Martin R. Oswald

For geometrical and temporal consistency, our approach explicitly creates a 3D point cloud representation of the scene and maintains dense 3D-2D correspondences across frames that reflect the geometric scene configuration inferred from the satellite view.

Image Generation

DeepVideoMVS: Multi-View Stereo on Video with Recurrent Spatio-Temporal Fusion

1 code implementation CVPR 2021 Arda Düzçeker, Silvano Galliani, Christoph Vogel, Pablo Speciale, Mihai Dusmanu, Marc Pollefeys

We propose an online multi-view depth prediction approach on posed video streams, where the scene geometry information computed in the previous time steps is propagated to the current time step in an efficient and geometrically plausible way.

Depth Estimation

Cross-Descriptor Visual Localization and Mapping

1 code implementation ICCV 2021 Mihai Dusmanu, Ondrej Miksik, Johannes L. Schönberger, Marc Pollefeys

Visual localization and mapping is the key technology underlying the majority of mixed reality and robotics systems.

Computer Vision Mixed Reality +1

DeFMO: Deblurring and Shape Recovery of Fast Moving Objects

5 code implementations CVPR 2021 Denys Rozumnyi, Martin R. Oswald, Vittorio Ferrari, Jiri Matas, Marc Pollefeys

We propose a method that, given a single image with its estimated background, outputs the object's appearance and position in a series of sub-frames as if captured by a high-speed camera (i. e. temporal super-resolution).

Deblurring Object Tracking +1

NeuralFusion: Online Depth Fusion in Latent Space

1 code implementation CVPR 2021 Silvan Weder, Johannes L. Schönberger, Marc Pollefeys, Martin R. Oswald

We present a novel online depth map fusion approach that learns depth map aggregation in a latent feature space.

Freetures: Localization in Signed Distance Function Maps

no code implementations19 Oct 2020 Alexander Millane, Helen Oleynikova, Christian Lanegger, Jeff Delmerico, Juan Nieto, Roland Siegwart, Marc Pollefeys, Cesar Cadena

Localization of a robotic system within a previously mapped environment is important for reducing estimation drift and for reusing previously built maps.


Weakly Supervised Learning of Multi-Object 3D Scene Decompositions Using Deep Shape Priors

no code implementations8 Oct 2020 Cathrin Elich, Martin R. Oswald, Marc Pollefeys, Joerg Stueckler

Our approach learns to decompose images of synthetic scenes with multiple objects on a planar surface into its constituent scene objects and to infer their 3D properties from a single view.

Decision Making Scene Understanding

Self-Supervised Learning of Non-Rigid Residual Flow and Ego-Motion

no code implementations22 Sep 2020 Ivan Tishchenko, Sandro Lombardi, Martin R. Oswald, Marc Pollefeys

Most of the current scene flow methods choose to model scene flow as a per point translation vector without differentiating between static and dynamic components of 3D motion.

Self-Supervised Learning Translation

HoloLens 2 Research Mode as a Tool for Computer Vision Research

1 code implementation25 Aug 2020 Dorin Ungureanu, Federica Bogo, Silvano Galliani, Pooja Sama, Xin Duan, Casey Meekhof, Jan Stühmer, Thomas J. Cashman, Bugra Tekin, Johannes L. Schönberger, Pawel Olszta, Marc Pollefeys

Mixed reality headsets, such as the Microsoft HoloLens 2, are powerful sensing devices with integrated compute capabilities, which makes it an ideal platform for computer vision research.

Computer Vision Mixed Reality

LIC-Fusion 2.0: LiDAR-Inertial-Camera Odometry with Sliding-Window Plane-Feature Tracking

no code implementations17 Aug 2020 Xingxing Zuo, Yulin Yang, Patrick Geneva, Jiajun Lv, Yong liu, Guoquan Huang, Marc Pollefeys

Only the tracked planar points belonging to the same plane will be used for plane initialization, which makes the plane extraction efficient and robust.


KAPLAN: A 3D Point Descriptor for Shape Completion

no code implementations31 Jul 2020 Audrey Richard, Ian Cherabier, Martin R. Oswald, Marc Pollefeys, Konrad Schindler

We present a novel 3D shape completion method that operates directly on unstructured point clouds, thus avoiding resource-intensive data structures like voxel grids.

3D Shape Reconstruction

Infrastructure-based Multi-Camera Calibration using Radial Projections

1 code implementation ECCV 2020 Yukai Lin, Viktor Larsson, Marcel Geppert, Zuzana Kukelova, Marc Pollefeys, Torsten Sattler

In particular, our approach is more robust than the naive approach of first estimating intrinsic parameters and pose per camera before refining the extrinsic parameters of the system.

Camera Calibration Self-Driving Cars +1

AdaLAM: Revisiting Handcrafted Outlier Detection

3 code implementations7 Jun 2020 Luca Cavalli, Viktor Larsson, Martin Ralf Oswald, Torsten Sattler, Marc Pollefeys

Local feature matching is a critical component of many computer vision pipelines, including among others Structure-from-Motion, SLAM, and Visual Localization.

Computer Vision Key Point Matching +2

OmniSLAM: Omnidirectional Localization and Dense Mapping for Wide-baseline Multi-camera Systems

no code implementations18 Mar 2020 Changhee Won, Hochang Seok, Zhaopeng Cui, Marc Pollefeys, Jongwoo Lim

In this paper, we present an omnidirectional localization and dense mapping system for a wide-baseline multiview stereo setup with ultra-wide field-of-view (FOV) fisheye cameras, which has a 360 degrees coverage of stereo observations of the environment.

Depth Estimation Visual Odometry

Multi-View Optimization of Local Feature Geometry

1 code implementation ECCV 2020 Mihai Dusmanu, Johannes L. Schönberger, Marc Pollefeys

In this work, we address the problem of refining the geometry of local image features from multiple views without known scene or camera geometry.

Camera Localization

Convolutional Occupancy Networks

4 code implementations ECCV 2020 Songyou Peng, Michael Niemeyer, Lars Mescheder, Marc Pollefeys, Andreas Geiger

Recently, implicit neural representations have gained popularity for learning-based 3D reconstruction.

3D Reconstruction

Self-Supervised Linear Motion Deblurring

1 code implementation10 Feb 2020 Peidong Liu, Joel Janai, Marc Pollefeys, Torsten Sattler, Andreas Geiger

Motion blurry images challenge many computer vision algorithms, e. g, feature detection, motion estimation, or object recognition.

Computer Vision Deblurring +4

Aerial Single-View Depth Completion with Image-Guided Uncertainty Estimation

2 code implementations17 Jan 2020 Lucas Teixeira, Martin R. Oswald, Marc Pollefeys, Margarita Chli

In this paper, we propose a depth completion and uncertainty estimation approach that better handles the challenges of aerial platforms, such as large viewpoint and depth variations, and limited computing resources.

Depth Completion Monocular Depth Estimation +1

Learned Multi-View Texture Super-Resolution

no code implementations14 Jan 2020 Audrey Richard, Ian Cherabier, Martin R. Oswald, Vagia Tsiminaki, Marc Pollefeys, Konrad Schindler

We present a super-resolution method capable of creating a high-resolution texture map for a virtual 3D object from a set of lower-resolution images of that object.

Image Super-Resolution Single Image Super Resolution

Reflection Separation using a Pair of Unpolarized and Polarized Images

1 code implementation NeurIPS 2019 Youwei Lyu, Zhaopeng Cui, Si Li, Marc Pollefeys, Boxin Shi

When we take photos through glass windows or doors, the transmitted background scene is often blended with undesirable reflection.

DIST: Rendering Deep Implicit Signed Distance Function with Differentiable Sphere Tracing

1 code implementation CVPR 2020 Shaohui Liu, yinda zhang, Songyou Peng, Boxin Shi, Marc Pollefeys, Zhaopeng Cui

We propose a differentiable sphere tracing algorithm to bridge the gap between inverse graphics methods and the recently proposed deep learning based implicit signed distance function.

Slanted Stixels: A way to represent steep streets

no code implementations2 Oct 2019 Daniel Hernandez-Juarez, Lukas Schneider, Pau Cebrian, Antonio Espinosa, David Vazquez, Antonio M. Lopez, Uwe Franke, Marc Pollefeys, Juan C. Moure

This work presents and evaluates a novel compact scene representation based on Stixels that infers geometric and semantic information.

Learned Semantic Multi-Sensor Depth Map Fusion

no code implementations2 Sep 2019 Denys Rozumnyi, Ian Cherabier, Marc Pollefeys, Martin R. Oswald

Our method learns sensor or algorithm properties jointly with semantic depth fusion and scene completion and can also be used as an expert system, e. g. to unify the strengths of various photometric stereo algorithms.

3D Reconstruction Denoising

To Learn or Not to Learn: Visual Localization from Essential Matrices

1 code implementation4 Aug 2019 Qunjie Zhou, Torsten Sattler, Marc Pollefeys, Laura Leal-Taixe

Using a classical feature-based approach within this framework, we show state-of-the-art performance.

Computer Vision Mixed Reality +3

3D Appearance Super-Resolution with Deep Learning

1 code implementation CVPR 2019 Yawei Li, Vagia Tsiminaki, Radu Timofte, Marc Pollefeys, Luc van Gool

Experimental results demonstrate that our proposed networks successfully incorporate the 3D geometric information and super-resolve the texture maps.


Robust Dense Mapping for Large-Scale Dynamic Environments

no code implementations7 May 2019 Ioan Andrei Bârsan, Peidong Liu, Marc Pollefeys, Andreas Geiger

We use both instance-aware semantic segmentation and sparse scene flow to classify objects as either background, moving, or potentially moving, thereby ensuring that the system is able to model objects with the potential to transition from static to dynamic, such as parked cars.

Semantic Segmentation Visual Odometry

H+O: Unified Egocentric Recognition of 3D Hand-Object Poses and Interactions

1 code implementation CVPR 2019 Bugra Tekin, Federica Bogo, Marc Pollefeys

Given a single RGB image, our model jointly estimates the 3D hand and object poses, models their interactions, and recognizes the object and action classes with a single feed-forward pass through a neural network.

Understanding the Limitations of CNN-based Absolute Camera Pose Regression

1 code implementation CVPR 2019 Torsten Sattler, Qunjie Zhou, Marc Pollefeys, Laura Leal-Taixe

We furthermore use our model to show that pose regression is more closely related to pose approximation via image retrieval than to accurate pose estimation via 3D structure.

Computer Vision Image Retrieval +4

Privacy Preserving Image-Based Localization

no code implementations CVPR 2019 Pablo Speciale, Johannes L. Schönberger, Sing Bing Kang, Sudipta N. Sinha, Marc Pollefeys

Current localization systems rely on the persistent storage of 3D point clouds of the scene to enable camera pose estimation, but such data reveals potentially sensitive scene information.

Image-Based Localization Mixed Reality +2

Incremental Visual-Inertial 3D Mesh Generation with Structural Regularities

4 code implementations4 Mar 2019 Antoni Rosinol, Torsten Sattler, Marc Pollefeys, Luca Carlone

We propose instead to tightly couple mesh regularization and state estimation by detecting and enforcing structural regularities in a novel factor-graph formulation.

3D Reconstruction Simultaneous Localization and Mapping

Episodic Curiosity through Reachability

1 code implementation ICLR 2019 Nikolay Savinov, Anton Raichuk, Raphaël Marinier, Damien Vincent, Marc Pollefeys, Timothy Lillicrap, Sylvain Gelly

One solution to this problem is to allow the agent to create rewards for itself - thus making rewards dense and more suitable for learning.

SurfelMeshing: Online Surfel-Based Mesh Reconstruction

1 code implementation1 Oct 2018 Thomas Schöps, Torsten Sattler, Marc Pollefeys

In contrast to most existing approaches, we do not fuse depth measurements in a volume but in a dense surfel cloud.

Night-to-Day Image Translation for Retrieval-based Localization

1 code implementation26 Sep 2018 Asha Anoosheh, Torsten Sattler, Radu Timofte, Marc Pollefeys, Luc van Gool

We then compare the daytime and translated night images to obtain a pose estimate for the night image using the known 6-DOF position of the closest day image.

Image Retrieval Style Generalization +2

Efficient 2D-3D Matching for Multi-Camera Visual Localization

no code implementations17 Sep 2018 Marcel Geppert, Peidong Liu, Zhaopeng Cui, Marc Pollefeys, Torsten Sattler

This results in a system that provides reliable and drift-less pose estimations for high speed autonomous driving.


Learning Priors for Semantic 3D Reconstruction

no code implementations ECCV 2018 Ian Cherabier, Johannes L. Schonberger, Martin R. Oswald, Marc Pollefeys, Andreas Geiger

In contrast to existing variational methods for semantic 3D reconstruction, our model is end-to-end trainable and captures more complex dependencies between the semantic labels and the 3D geometry.

3D Reconstruction

VSO: Visual Semantic Odometry

no code implementations ECCV 2018 Konstantinos-Nektarios Lianos, Johannes L. Schonberger, Marc Pollefeys, Torsten Sattler

Robust data association is a core problem of visual odometry, where image-to-image correspondences provide constraints for camera pose and map estimation.

Autonomous Driving Visual Odometry

A Dataset of Flash and Ambient Illumination Pairs from the Crowd

no code implementations ECCV 2018 Yagiz Aksoy, Changil Kim, Petr Kellnhofer, Sylvain Paris, Mohamed Elgharib, Marc Pollefeys, Wojciech Matusik

We present a dataset of thousands of ambient and flash illumination pairs to enable studying flash photography and other applications that can benefit from having separate illuminations.

Computer Vision

Semantic Match Consistency for Long-Term Visual Localization

no code implementations ECCV 2018 Carl Toft, Erik Stenborg, Lars Hammarstrand, Lucas Brynte, Marc Pollefeys, Torsten Sattler, Fredrik Kahl

Robust and accurate visual localization across large appearance variations due to changes in time of day, seasons, or changes of the environment is a challenging problem which is of importance to application areas such as navigation of autonomous robots.

Visual Localization

Hybrid Scene Compression for Visual Localization

no code implementations CVPR 2019 Federico Camposeco, Andrea Cohen, Marc Pollefeys, Torsten Sattler

Besides outperforming previous compression techniques in terms of pose accuracy under the same memory constraints, our compression scheme itself is also more efficient.

Computer Vision Quantization +2

Augmenting Crowd-Sourced 3D Reconstructions Using Semantic Detections

no code implementations CVPR 2018 True Price, Johannes L. Schönberger, Zhen Wei, Marc Pollefeys, Jan-Michael Frahm

Image-based 3D reconstruction for Internet photo collections has become a robust technology to produce impressive virtual representations of real-world scenes.

3D Reconstruction

Semantic Visual Localization

no code implementations CVPR 2018 Johannes L. Schönberger, Marc Pollefeys, Andreas Geiger, Torsten Sattler

Robust visual localization under a wide range of viewing conditions is a fundamental problem in computer vision.

Computer Vision Visual Localization

From Point Clouds to Mesh Using Regression

no code implementations ICCV 2017 Lubor Ladicky, Olivier Saurer, SoHyeon Jeong, Fabio Maninchedda, Marc Pollefeys

Surface reconstruction from a point cloud is a standard subproblem in many algorithms for dense 3D reconstruction from RGB images or depth maps.

3D Reconstruction Surface Reconstruction

Slanted Stixels: Representing San Francisco's Steepest Streets

1 code implementation17 Jul 2017 Daniel Hernandez-Juarez, Lukas Schneider, Antonio Espinosa, David Vázquez, Antonio M. López, Uwe Franke, Marc Pollefeys, Juan C. Moure

In this work we present a novel compact scene representation based on Stixels that infers geometric and semantic information.

Information-Flow Matting

1 code implementation CVPR 2017 Yağız Aksoy, Tunç Ozan Aydın, Marc Pollefeys

Our resulting novel linear system formulation can be solved in closed-form and is robust against several fundamental challenges of natural matting such as holes and remote intricate structures.

Image Matting

SGM-Nets: Semi-Global Matching With Neural Networks

no code implementations CVPR 2017 Akihito Seki, Marc Pollefeys

Moreover, we propose a novel SGM parameterization, which deploys different penalties depending on either positive or negative disparity changes in order to represent the object structures more discriminatively.

Comparative Evaluation of Hand-Crafted and Learned Local Features

1 code implementation Conference on Computer Vision and Pattern Recognition 2017 Johannes L. Sch¨onberger, Hans Hardmeier, Torsten Sattler, Marc Pollefeys

In terms of matching performance, we evaluate the different descriptors regarding standard criteria. However, considering matching performance in isolation only provides an incomplete measure of a descriptor’s quality.

Computer Vision Image Retrieval

Consensus Maximization With Linear Matrix Inequality Constraints

no code implementations CVPR 2017 Pablo Speciale, Danda Pani Paudel, Martin R. Oswald, Till Kroeger, Luc van Gool, Marc Pollefeys

While randomized methods like RANSAC are fast, they do not guarantee global optimality and fail to manage large amounts of outliers.

Computer Vision

Toroidal Constraints for Two-Point Localization Under High Outlier Ratios

no code implementations CVPR 2017 Federico Camposeco, Torsten Sattler, Andrea Cohen, Andreas Geiger, Marc Pollefeys

Adding the knowledge of direction of triangulation, we are able to approximate the position of the camera from two matches alone.

Pose Estimation

Designing Effective Inter-Pixel Information Flow for Natural Image Matting

no code implementations CVPR 2017 Yagiz Aksoy, Tunc Ozan Aydin, Marc Pollefeys

Our resulting novel linear system formulation can be solved in closed-form and is robust against several fundamental challenges in natural matting such as holes and remote intricate structures.

Image Matting

Matching neural paths: transfer from recognition to correspondence search

no code implementations NeurIPS 2017 Nikolay Savinov, Lubor Ladicky, Marc Pollefeys

We propose to use a hierarchical semantic representation of the objects, coming from a convolutional neural network, to solve this ambiguity. A new Large-scale Point Cloud Classification Benchmark

1 code implementation12 Apr 2017 Timo Hackel, Nikolay Savinov, Lubor Ladicky, Jan D. Wegner, Konrad Schindler, Marc Pollefeys

With the massive data set presented in this paper, we aim at closing this data gap to help unleash the full potential of deep learning methods for 3D labelling tasks.

3D Point Cloud Classification Classification +6

The Stixel world: A medium-level representation of traffic scenes

no code implementations2 Apr 2017 Marius Cordts, Timo Rehfeld, Lukas Schneider, David Pfeiffer, Markus Enzweiler, Stefan Roth, Marc Pollefeys, Uwe Franke

We believe this challenge should be faced by introducing a representation of the sensory data that provides compressed and structured access to all relevant visual content of the scene.

Autonomous Vehicles object-detection +1

Semantically Guided Depth Upsampling

no code implementations2 Aug 2016 Nick Schneider, Lukas Schneider, Peter Pinggera, Uwe Franke, Marc Pollefeys, Christoph Stiller

We present a novel method for accurate and efficient up- sampling of sparse depth data, guided by high-resolution imagery.

Edge Detection Scene Labeling

Sparse to Dense 3D Reconstruction From Rolling Shutter Images

no code implementations CVPR 2016 Olivier Saurer, Marc Pollefeys, Gim Hee Lee

It is well known that the rolling shutter effect in images captured with a moving rolling shutter camera causes inaccuracies to 3D reconstructions.

3D Reconstruction

Do It Yourself Hyperspectral Imaging With Everyday Digital Cameras

no code implementations CVPR 2016 Seoung Wug Oh, Michael S. Brown, Marc Pollefeys, Seon Joo Kim

In particular, due to the differences in spectral sensitivities of the cameras, different cameras yield different RGB measurements for the same spectral signal.

Large-Scale Location Recognition and the Geometric Burstiness Problem

1 code implementation CVPR 2016 Torsten Sattler, Michal Havlena, Konrad Schindler, Marc Pollefeys

Visual location recognition is the task of determining the place depicted in a query image from a given database of geo-tagged images.

Image Retrieval Re-Ranking

Automatic 3D Reconstruction of Manifold Meshes via Delaunay Triangulation and Mesh Sweeping

no code implementations21 Apr 2016 Andrea Romanoni, Amaël Delaunoy, Marc Pollefeys, Matteo Matteucci

In this paper we propose a new approach to incrementally initialize a manifold surface for automatic 3D reconstruction from images.

3D Reconstruction

TI-POOLING: transformation-invariant pooling for feature learning in Convolutional Neural Networks

1 code implementation CVPR 2016 Dmitry Laptev, Nikolay Savinov, Joachim M. Buhmann, Marc Pollefeys

This more efficient use of training data results in better performance on popular benchmark datasets with smaller number of parameters when comparing to standard convolutional neural networks with dataset augmentation and to other baselines.

Semantic 3D Reconstruction with Continuous Regularization and Ray Potentials Using a Visibility Consistency Constraint

1 code implementation CVPR 2016 Nikolay Savinov, Christian Haene, Lubor Ladicky, Marc Pollefeys

We propose an approach for dense semantic 3D reconstruction which uses a data term that is defined as potentials over viewing rays, combined with continuous surface area penalization.

3D Reconstruction

Merging the Unmatchable: Stitching Visually Disconnected SfM Models

no code implementations ICCV 2015 Andrea Cohen, Torsten Sattler, Marc Pollefeys

An important variant of this problem is the case in which individual sides of a building can be reconstructed but not joined due to the missing visual overlap.

Non-Parametric Structure-Based Calibration of Radially Symmetric Cameras

no code implementations ICCV 2015 Federico Camposeco, Torsten Sattler, Marc Pollefeys

As a second step, we obtain the calibration by finding the translation of the camera center using an ordering constraint.


Entropy Minimization for Convex Relaxation Approaches

no code implementations ICCV 2015 Mohamed Souiai, Martin R. Oswald, Youngwook Kee, Junmo Kim, Marc Pollefeys, Daniel Cremers

Despite their enormous success in solving hard combinatorial problems, convex relaxation approaches often suffer from the fact that the computed solutions are far from binary and that subsequent heuristic binarization may substantially degrade the quality of computed solutions.

Binarization Computer Vision +1

Capturing Hands in Action using Discriminative Salient Points and Physics Simulation

2 code implementations6 Jun 2015 Dimitrios Tzionas, Luca Ballan, Abhilash Srikantha, Pablo Aponte, Marc Pollefeys, Juergen Gall

Hand motion capture is a popular research field, recently gaining more attention due to the ubiquity of RGB-D sensors.

Scalable Structure From Motion for Densely Sampled Videos

no code implementations CVPR 2015 Benjamin Resch, Hendrik P. A. Lensch, Oliver Wang, Marc Pollefeys, Alexander Sorkine-Hornung

Videos consisting of thousands of high resolution frames are challenging for existing structure from motion (SfM) and simultaneous-localization and mapping (SLAM) techniques.

Pose Estimation Simultaneous Localization and Mapping

Direction Matters: Depth Estimation With a Surface Normal Classifier

no code implementations CVPR 2015 Christian Hane, Lubor Ladicky, Marc Pollefeys

In this work we make use of recent advances in data driven classification to improve standard approaches for binocular stereo matching and single view depth estimation.

Depth Estimation Stereo Matching +1

Learning the Matching Function

no code implementations2 Feb 2015 Ľubor Ladický, Christian Häne, Marc Pollefeys

In this paper we propose a method, which learns the matching function, that automatically finds the space of allowed changes in visual appearance, such as due to the motion blur, chromatic distortions, different colour calibration or seasonal changes.

Change Detection Optical Flow Estimation +2

Pulling Things out of Perspective

no code implementations CVPR 2014 Lubor Ladicky, Jianbo Shi, Marc Pollefeys

The limitations of current state-of-the-art methods for single-view depth estimation and semantic segmentations are closely tied to the property of perspective geometry, that the perceived size of the objects scales inversely with the distance.

Depth Estimation Semantic Segmentation

Relative Pose Estimation for a Multi-Camera System with Known Vertical Direction

no code implementations CVPR 2014 Gim Hee Lee, Marc Pollefeys, Friedrich Fraundorfer

In this paper, we present our minimal 4-point and linear 8-point algorithms to estimate the relative pose of a multi-camera system with known vertical directions, i. e. known absolute roll and pitch angles.

Pose Estimation

Class Specific 3D Object Shape Priors Using Surface Normals

no code implementations CVPR 2014 Christian Hane, Nikolay Savinov, Marc Pollefeys

Dense 3D reconstruction of real world objects containing textureless, reflective and specular parts is a challenging task.

3D Reconstruction

Photometric Bundle Adjustment for Dense Multi-View 3D Modeling

1 code implementation CVPR 2014 Amael Delaunoy, Marc Pollefeys

Motivated by a Bayesian vision of the 3D multi-view reconstruction from images problem, we propose a dense 3D reconstruction technique that jointly refines the shape and the camera parameters of a scene by minimizing the photometric reprojection error between a generated model and the observed images, hence considering all pixels in the original images.

3D Reconstruction Camera Calibration

Efficient Structured Parsing of Facades Using Dynamic Programming

no code implementations CVPR 2014 Andrea Cohen, Alexander G. Schwing, Marc Pollefeys

We propose a sequential optimization technique for segmenting a rectified image of a facade into semantic categories.

General Classification

Turning Mobile Phones into 3D Scanners

no code implementations CVPR 2014 Kalin Kolev, Petri Tanskanen, Pablo Speciale, Marc Pollefeys

In this paper, we propose an efficient and accurate scheme for the integration of multiple stereo-based depth measurements.

3D Reconstruction

Joint 3D Scene Reconstruction and Class Segmentation

no code implementations CVPR 2013 Christian Hane, Christopher Zach, Andrea Cohen, Roland Angst, Marc Pollefeys

Image segmentations provide geometric cues about which surface orientations are more likely to appear at a certain location in space whereas a dense 3D reconstruction yields a suitable regularization for the segmentation problem by lifting the labeling from 2D images to 3D space.

3D Reconstruction 3D Scene Reconstruction +1

Radial Distortion Self-Calibration

no code implementations CVPR 2013 Jose Henrique Brito, Roland Angst, Kevin Koser, Marc Pollefeys

In cameras with radial distortion, straight lines in space are in general mapped to curves in the image.

Motion Estimation for Self-Driving Cars with a Generalized Camera

no code implementations CVPR 2013 Gim Hee Lee, Friedrich Faundorfer, Marc Pollefeys

By modeling the multicamera system as a generalized camera and applying the non-holonomic motion constraint of a car, we show that this leads to a novel 2-point minimal solution for the generalized essential matrix where the full relative motion including metric scale can be obtained.

Motion Estimation Self-Driving Cars

City-Scale Change Detection in Cadastral 3D Models Using Images

no code implementations CVPR 2013 Aparna Taneja, Luca Ballan, Marc Pollefeys

In this paper, we propose a method to detect changes in the geometry of a city using panoramic images captured by a car driving around the city.

Change Detection

Globally Convergent Dual MAP LP Relaxation Solvers using Fenchel-Young Margins

no code implementations NeurIPS 2012 Alex Schwing, Tamir Hazan, Marc Pollefeys, Raquel Urtasun

While finding the exact solution for the MAP inference problem is intractable for many real-world tasks, MAP LP relaxations have been shown to be very effective in practice.

Gated Softmax Classification

no code implementations NeurIPS 2010 Roland Memisevic, Christopher Zach, Marc Pollefeys, Geoffrey E. Hinton

We describe a log-bilinear" model that computes class probabilities by combining an input vector multiplicatively with a vector of binary latent variables.

Classification General Classification

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