641 citations · 3k across the 58 of their papers we have counts for
15 papers · 1 filter
Boosting Monocular Depth Estimation with Lightweight 3D Point Fusion
Lam Huynh, Phong Nguyen-Ha, Jiri Matas +2
In this paper, we propose enhancing monocular depth estimation by adding 3D points as depth guidance. Unlike existing depth completion methods, our approach performs well on extrem…
FMODetect: Robust Detection of Fast Moving Objects
Denys Rozumnyi, Jiri Matas, Filip Sroubek +2
We propose the first learning-based approach for fast moving objects detection. Such objects are highly blurred and move over large distances within one video frame. Fast moving ob…
DeFMO: Deblurring and Shape Recovery of Fast Moving Objects
Denys Rozumnyi, Martin R. Oswald, Vittorio Ferrari +2
Objects moving at high speed appear significantly blurred when captured with cameras. The blurry appearance is especially ambiguous when the object has complex shape or texture. In…
Efficient Initial Pose-graph Generation for Global SfM
Daniel Barath, Dmytro Mishkin, Ivan Eichhardt +2
We propose ways to speed up the initial pose-graph generation for global Structure-from-Motion algorithms. To avoid forming tentative point correspondences by FLANN and geometric v…
Fast Fourier Intrinsic Network
Yanlin Qian, Miaojing Shi, Joni-Kristian Kämäräinen +1
We address the problem of decomposing an image into albedo and shading. We propose the Fast Fourier Intrinsic Network, FFI-Net in short, that operates in the spectral domain, split…
RGBD-Net: Predicting color and depth images for novel views synthesis
Phong Nguyen-Ha, Animesh Karnewar, Lam Huynh +3
We propose a new cascaded architecture for novel view synthesis, called RGBD-Net, which consists of two core components: a hierarchical depth regression network and a depth-aware g…
Robust Audio-Based Vehicle Counting in Low-to-Moderate Traffic Flow
Slobodan Djukanović, Jiři Matas, Tuomas Virtanen
The paper presents a method for audio-based vehicle counting (VC) in low-to-moderate traffic using one-channel sound. We formulate VC as a regression problem, i.e., we predict the…
BOP Challenge 2020 on 6D Object Localization
Tomas Hodan, Martin Sundermeyer, Bertram Drost +5
This paper presents the evaluation methodology, datasets, and results of the BOP Challenge 2020, the third in a series of public competitions organized with the goal to capture the…
ArXiving Before Submission Helps Everyone
Dmytro Mishkin, Amy Tabb, Jiri Matas
We claim, and present evidence, that allowing arXiv publication before a conference or journal submission benefits researchers, especially early career, as well as the whole scient…
Text Recognition -- Real World Data and Where to Find Them
Klára Janoušková, Jiri Matas, Lluis Gomez +1
We present a method for exploiting weakly annotated images to improve text extraction pipelines. The approach uses an arbitrary end-to-end text recognition system to obtain text re…
Learning Surrogates via Deep Embedding
Yash Patel, Tomas Hodan, Jiri Matas
This paper proposes a technique for training a neural network by minimizing a surrogate loss that approximates the target evaluation metric, which may be non-differentiable. The su…
Guiding Monocular Depth Estimation Using Depth-Attention Volume
Lam Huynh, Phong Nguyen-Ha, Jiri Matas +2
Recovering the scene depth from a single image is an ill-posed problem that requires additional priors, often referred to as monocular depth cues, to disambiguate different 3D inte…
EPOS: Estimating 6D Pose of Objects with Symmetries
Tomas Hodan, Daniel Barath, Jiri Matas
We present a new method for estimating the 6D pose of rigid objects with available 3D models from a single RGB input image. The method is applicable to a broad range of objects, in…
A Benchmark for Temporal Color Constancy
Yanlin Qian, Jani Käpylä, Joni-Kristian Kämäräinen +2
Temporal Color Constancy (CC) is a recently proposed approach that challenges the conventional single-frame color constancy. The conventional approach is to use a single frame - sh…
Image Matching across Wide Baselines: From Paper to Practice
Yuhe Jin, Dmytro Mishkin, Anastasiia Mishchuk +4
We introduce a comprehensive benchmark for local features and robust estimation algorithms, focusing on the downstream task -- the accuracy of the reconstructed camera pose -- as o…