499 citations · 2.2k across the 41 of their papers we have counts for
52 papers
HuManiFlow: Ancestor-Conditioned Normalising Flows on SO(3) Manifolds for Human Pose and Shape Distribution Estimation
Akash Sengupta, Ignas Budvytis, Roberto Cipolla
Monocular 3D human pose and shape estimation is an ill-posed problem since multiple 3D solutions can explain a 2D image of a subject. Recent approaches predict a probability distri…
SFD2: Semantic-guided Feature Detection and Description
Fei Xue, Ignas Budvytis, Roberto Cipolla
Visual localization is a fundamental task for various applications including autonomous driving and robotics. Prior methods focus on extracting large amounts of often redundant loc…
IMP: Iterative Matching and Pose Estimation with Adaptive Pooling
Fei Xue, Ignas Budvytis, Roberto Cipolla
Previous methods solve feature matching and pose estimation using a two-stage process by first finding matches and then estimating the pose. As they ignore the geometric relationsh…
Model-Based Imitation Learning for Urban Driving
Anthony Hu, Gianluca Corrado, Nicolas Griffiths +6
An accurate model of the environment and the dynamic agents acting in it offers great potential for improving motion planning. We present MILE: a Model-based Imitation LEarning app…
A CNN Based Approach for the Point-Light Photometric Stereo Problem
Fotios Logothetis, Roberto Mecca, Ignas Budvytis +1
Reconstructing the 3D shape of an object using several images under different light sources is a very challenging task, especially when realistic assumptions such as light propagat…
IronDepth: Iterative Refinement of Single-View Depth using Surface Normal and its Uncertainty
Gwangbin Bae, Ignas Budvytis, Roberto Cipolla
Single image surface normal estimation and depth estimation are closely related problems as the former can be calculated from the latter. However, the surface normals computed from…
DigiFace-1M: 1 Million Digital Face Images for Face Recognition
Gwangbin Bae, Martin de La Gorce, Tadas Baltrusaitis +5
State-of-the-art face recognition models show impressive accuracy, achieving over 99.8% on Labeled Faces in the Wild (LFW) dataset. Such models are trained on large-scale datasets…
SPARC: Sparse Render-and-Compare for CAD model alignment in a single RGB image
Florian Langer, Gwangbin Bae, Ignas Budvytis +1
Estimating 3D shapes and poses of static objects from a single image has important applications for robotics, augmented reality and digital content creation. Often this is done thr…
FIND: An Unsupervised Implicit 3D Model of Articulated Human Feet
Oliver Boyne, James Charles, Roberto Cipolla
In this paper we present a high fidelity and articulated 3D human foot model. The model is parameterised by a disentangled latent code in terms of shape, texture and articulated po…
Contrastive Unsupervised Learning of World Model with Invariant Causal Features
Rudra P. K. Poudel, Harit Pandya, Roberto Cipolla
In this paper we present a world model, which learns causal features using the invariance principle. In particular, we use contrastive unsupervised learning to learn the invariant…
Discrete neural representations for explainable anomaly detection
Stanislaw Szymanowicz, James Charles, Roberto Cipolla
The aim of this work is to detect and automatically generate high-level explanations of anomalous events in video. Understanding the cause of an anomalous event is crucial as the r…
Multi-View Depth Estimation by Fusing Single-View Depth Probability with Multi-View Geometry
Gwangbin Bae, Ignas Budvytis, Roberto Cipolla
Multi-view depth estimation methods typically require the computation of a multi-view cost-volume, which leads to huge memory consumption and slow inference. Furthermore, multi-vie…
Probabilistic Estimation of 3D Human Shape and Pose with a Semantic Local Parametric Model
Akash Sengupta, Ignas Budvytis, Roberto Cipolla
This paper addresses the problem of 3D human body shape and pose estimation from RGB images. Some recent approaches to this task predict probability distributions over human body m…
Leveraging Geometry for Shape Estimation from a Single RGB Image
Florian Langer, Ignas Budvytis, Roberto Cipolla
Predicting 3D shapes and poses of static objects from a single RGB image is an important research area in modern computer vision. Its applications range from augmented reality to r…
Hierarchical Kinematic Probability Distributions for 3D Human Shape and Pose Estimation from Images in the Wild
Akash Sengupta, Ignas Budvytis, Roberto Cipolla
This paper addresses the problem of 3D human body shape and pose estimation from an RGB image. This is often an ill-posed problem, since multiple plausible 3D bodies may match the…
Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal Estimation
Gwangbin Bae, Ignas Budvytis, Roberto Cipolla
Surface normal estimation from a single image is an important task in 3D scene understanding. In this paper, we address two limitations shared by the existing methods: the inabilit…
X-MAN: Explaining multiple sources of anomalies in video
Stanislaw Szymanowicz, James Charles, Roberto Cipolla
Our objective is to detect anomalies in video while also automatically explaining the reason behind the detector's response. In a practical sense, explainability is crucial for thi…
LUCES: A Dataset for Near-Field Point Light Source Photometric Stereo
Roberto Mecca, Fotios Logothetis, Ignas Budvytis +1
Three-dimensional reconstruction of objects from shading information is a challenging task in computer vision. As most of the approaches facing the Photometric Stereo problem use s…
FIERY: Future Instance Prediction in Bird's-Eye View from Surround Monocular Cameras
Anthony Hu, Zak Murez, Nikhil Mohan +5
Driving requires interacting with road agents and predicting their future behaviour in order to navigate safely. We present FIERY: a probabilistic future prediction model in bird's…
Probabilistic 3D Human Shape and Pose Estimation from Multiple Unconstrained Images in the Wild
Akash Sengupta, Ignas Budvytis, Roberto Cipolla
This paper addresses the problem of 3D human body shape and pose estimation from RGB images. Recent progress in this field has focused on single images, video or multi-view images…
Synthetic Training for Accurate 3D Human Pose and Shape Estimation in the Wild
Akash Sengupta, Ignas Budvytis, Roberto Cipolla
This paper addresses the problem of monocular 3D human shape and pose estimation from an RGB image. Despite great progress in this field in terms of pose prediction accuracy, state…
A CNN Based Approach for the Near-Field Photometric Stereo Problem
Fotios Logothetis, Ignas Budvytis, Roberto Mecca +1
Reconstructing the 3D shape of an object using several images under different light sources is a very challenging task, especially when realistic assumptions such as light propagat…
Embodied Visual Navigation with Automatic Curriculum Learning in Real Environments
Steven D. Morad, Roberto Mecca, Rudra P. K. Poudel +2
We present NavACL, a method of automatic curriculum learning tailored to the navigation task. NavACL is simple to train and efficiently selects relevant tasks using geometric featu…
PX-NET: Simple and Efficient Pixel-Wise Training of Photometric Stereo Networks
Fotios Logothetis, Ignas Budvytis, Roberto Mecca +1
Retrieving accurate 3D reconstructions of objects from the way they reflect light is a very challenging task in computer vision. Despite more than four decades since the definition…