18 citations · 28 across the 20 of their papers we have counts for
33 papers
FLIGHT: Fibonacci Lattice-based Inference for Geometric Heading in real-Time
David Dirnfeld, Fabien Delattre, Pedro Miraldo +1
Estimating camera motion from monocular video is a fundamental problem in computer vision, central to tasks such as SLAM, visual odometry, and structure-from-motion. Existing metho…
LASER: Layer-wise Scale Alignment for Training-Free Streaming 4D Reconstruction
Tianye Ding, Yiming Xie, Yiqing Liang +3
Recent feed-forward reconstruction models like VGGT and achieve impressive reconstruction quality but cannot process streaming videos due to quadratic memory complexity, limi…
RAPTR: Radar-based 3D Pose Estimation using Transformer
Sorachi Kato, Ryoma Yataka, Pu Perry Wang +3
Radar-based indoor 3D human pose estimation typically relied on fine-grained 3D keypoint labels, which are costly to obtain especially in complex indoor settings involving clutter,…
SurfR: Surface Reconstruction with Multi-scale Attention
Siddhant Ranade, Gonçalo Dias Pais, Ross Tyler Whitaker +3
We propose a fast and accurate surface reconstruction algorithm for unorganized point clouds using an implicit representation. Recent learning methods are either single-object repr…
A Probability-guided Sampler for Neural Implicit Surface Rendering
Gonçalo Dias Pais, Valter Piedade, Moitreya Chatterjee +2
Several variants of Neural Radiance Fields (NeRFs) have significantly improved the accuracy of synthesized images and surface reconstruction of 3D scenes/objects. In all of these m…
FreBIS: Frequency-Based Stratification for Neural Implicit Surface Representations
Naoko Sawada, Pedro Miraldo, Suhas Lohit +2
Neural implicit surface representation techniques are in high demand for advancing technologies in augmented reality/virtual reality, digital twins, autonomous navigation, and many…
Gear-NeRF: Free-Viewpoint Rendering and Tracking with Motion-aware Spatio-Temporal Sampling
Xinhang Liu, Yu-Wing Tai, Chi-Keung Tang +3
Extensions of Neural Radiance Fields (NeRFs) to model dynamic scenes have enabled their near photo-realistic, free-viewpoint rendering. Although these methods have shown some poten…
Oriented-grid Encoder for 3D Implicit Representations
Arihant Gaur, G. Dias Pais, Pedro Miraldo
Encoding 3D points is one of the primary steps in learning-based implicit scene representation. Using features that gather information from neighbors with multi-resolution grids ha…
BANSAC: A dynamic BAyesian Network for adaptive SAmple Consensus
Valter Piedade, Pedro Miraldo
RANSAC-based algorithms are the standard techniques for robust estimation in computer vision. These algorithms are iterative and computationally expensive; they alternate between r…
Robust Frame-to-Frame Camera Rotation Estimation in Crowded Scenes
Fabien Delattre, David Dirnfeld, Phat Nguyen +4
We present an approach to estimating camera rotation in crowded, real-world scenes from handheld monocular video. While camera rotation estimation is a well-studied problem, no pre…
An observer cascade for velocity and multiple line estimation
André Mateus, Pedro U. Lima, Pedro Miraldo
Previous incremental estimation methods consider estimating a single line, requiring as many observers as the number of lines to be mapped. This leads to the need for having at lea…
Solving the Discrete Euler-Arnold Equations for the Generalized Rigid Body Motion
Joao R. Cardoso, Pedro Miraldo
We propose three iterative methods for solving the Moser-Veselov equation, which arises in the discretization of the Euler-Arnold differential equations governing the motion of a g…
On Incremental Structure-from-Motion using Lines
André Mateus, Omar Tahri, A. Pedro Aguiar +2
Humans tend to build environments with structure, which consists of mainly planar surfaces. From the intersection of planar surfaces arise straight lines. Lines have more degrees-o…
Mapping of Sparse 3D Data using Alternating Projection
Siddhant Ranade, Xin Yu, Shantnu Kakkar +2
We propose a novel technique to register sparse 3D scans in the absence of texture. While existing methods such as KinectFusion or Iterative Closest Points (ICP) heavily rely on de…
Active Depth Estimation: Stability Analysis and its Applications
Romulo T. Rodrigues, Pedro Miraldo, Dimos V. Dimarogonas +1
Recovering the 3D structure of the surrounding environment is an essential task in any vision-controlled Structure-from-Motion (SfM) scheme. This paper focuses on the theoretical p…
A Framework for Depth Estimation and Relative Localization of Ground Robots using Computer Vision
Romulo T. Rodrigues, Pedro Miraldo, Dimos V. Dimarogonas +1
The 3D depth estimation and relative pose estimation problem within a decentralized architecture is a challenging problem that arises in missions that require coordination among mu…
Can generalised relative pose estimation solve sparse 3D registration?
Siddhant Ranade, Xin Yu, Shantnu Kakkar +2
Popular 3D scan registration projects, such as Stanford digital Michelangelo or KinectFusion, exploit the high-resolution sensor data for scan alignment. It is particularly challen…
POSEAMM: A Unified Framework for Solving Pose Problems using an Alternating Minimization Method
Joao Campos, Joao R. Cardoso, Pedro Miraldo
Pose estimation is one of the most important problems in computer vision. It can be divided in two different categories -- absolute and relative -- and may involve two different ty…
Minimal Solvers for Mini-Loop Closures in 3D Multi-Scan Alignment
Pedro Miraldo, Surojit Saha, Srikumar Ramalingam
3D scan registration is a classical, yet a highly useful problem in the context of 3D sensors such as Kinect and Velodyne. While there are several existing methods, the techniques…
3DRegNet: A Deep Neural Network for 3D Point Registration
G. Dias Pais, Srikumar Ramalingam, Venu Madhav Govindu +3
We present 3DRegNet, a novel deep learning architecture for the registration of 3D scans. Given a set of 3D point correspondences, we build a deep neural network to address the fol…
Active Estimation of 3D Lines in Spherical Coordinates
André Mateus, Omar Tahri, Pedro Miraldo
Straight lines are common features in human made environments, which makes them a frequently explored feature for control applications. Many control schemes, like Visual Servoing,…
OmniDRL: Robust Pedestrian Detection using Deep Reinforcement Learning on Omnidirectional Cameras
G. Dias Pais, Tiago J. Dias, Jacinto C. Nascimento +1
Pedestrian detection is one of the most explored topics in computer vision and robotics. The use of deep learning methods allowed the development of new and highly competitive algo…
A Minimal Closed-Form Solution for Multi-Perspective Pose Estimation using Points and Lines
Pedro Miraldo, Tiago Dias, Srikumar Ramalingam
We propose a minimal solution for pose estimation using both points and lines for a multi-perspective camera. In this paper, we treat the multi-perspective camera as a collection o…
Active Structure-from-Motion for 3D Straight Lines
André Mateus, Omar Tahri, Pedro Miraldo
A reliable estimation of 3D parameters is a must for several applications like planning and control. Included in the latter is the Image-Based Visual Servoing, whose control scheme…