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09/14/2023
Looking at words and points with attention: a benchmark for text-to-shape coherence
While text-conditional 3D object generation and manipulation have seen r...
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07/27/2023
Learning Depth Estimation for Transparent and Mirror Surfaces
Inferring the depth of transparent or mirror (ToM) surfaces represents a...
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04/20/2023
ReLight My NeRF: A Dataset for Novel View Synthesis and Relighting of Real World Objects
In this paper, we focus on the problem of rendering novel views from a N...
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04/06/2023
Exploiting the Complementarity of 2D and 3D Networks to Address Domain-Shift in 3D Semantic Segmentation
3D semantic segmentation is a critical task in many real-world applicati...
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02/10/2023
Deep Learning on Implicit Neural Representations of Shapes
Implicit Neural Representations (INRs) have emerged in the last few year...
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01/26/2023
Learning Good Features to Transfer Across Tasks and Domains
Availability of labelled data is the major obstacle to the deployment of...
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01/19/2023
Booster: a Benchmark for Depth from Images of Specular and Transparent Surfaces
Estimating depth from images nowadays yields outstanding results, both i...
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11/24/2022
ScanNeRF: a Scalable Benchmark for Neural Radiance Fields
In this paper, we propose the first-ever real benchmark thought for eval...
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10/15/2022
Self-Distillation for Unsupervised 3D Domain Adaptation
Point cloud classification is a popular task in 3D vision. However, prev...
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09/01/2022
Cross-Spectral Neural Radiance Fields
We propose X-NeRF, a novel method to learn a Cross-Spectral scene repres...
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06/14/2022
RGB-Multispectral Matching: Dataset, Learning Methodology, Evaluation
We address the problem of registering synchronized color (RGB) and multi...
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06/10/2022
Learning the Space of Deep Models
Embedding of large but redundant data, such as images or text, in a hier...
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06/09/2022
Open Challenges in Deep Stereo: the Booster Dataset
We present a novel high-resolution and challenging stereo dataset framin...
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10/28/2021
Neural Disparity Refinement for Arbitrary Resolution Stereo
We introduce a novel architecture for neural disparity refinement aimed ...
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10/21/2021
RefRec: Pseudo-labels Refinement via Shape Reconstruction for Unsupervised 3D Domain Adaptation
Unsupervised Domain Adaptation (UDA) for point cloud classification is a...
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10/13/2021
Plugging Self-Supervised Monocular Depth into Unsupervised Domain Adaptation for Semantic Segmentation
Although recent semantic segmentation methods have made remarkable progr...
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10/06/2021
Shallow Features Guide Unsupervised Domain Adaptation for Semantic Segmentation at Class Boundaries
Although deep neural networks have achieved remarkable results for the t...
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12/24/2020
Effective Deployment of CNNs for 3DoF Pose Estimation and Grasping in Industrial Settings
In this paper we investigate how to effectively deploy deep learning in ...
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12/04/2020
SAFFIRE: System for Autonomous Feature Filtering and Intelligent ROI Estimation
This work introduces a new framework, named SAFFIRE, to automatically ex...
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11/06/2020
Learning to Orient Surfaces by Self-supervised Spherical CNNs
Defining and reliably finding a canonical orientation for 3D surfaces is...
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07/10/2020
Continual Adaptation for Deep Stereo
Depth estimation from stereo images is carried out with unmatched result...
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03/31/2020
Distilled Semantics for Comprehensive Scene Understanding from Videos
Whole understanding of the surroundings is paramount to autonomous syste...
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11/06/2019
Boosting Object Recognition in Point Clouds by Saliency Detection
Object recognition in 3D point clouds is a challenging task, mainly when...
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10/11/2019
Shooting Labels: 3D Semantic Labeling by Virtual Reality
Availability of a few, large-size, annotated datasets, like ImageNet, Pa...
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09/15/2019
Learning an Effective Equivariant 3D Descriptor Without Supervision
Establishing correspondences between 3D shapes is a fundamental task in ...
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09/15/2019
Performance Evaluation of Learned 3D Features
Matching surfaces is a challenging 3D Computer Vision problem typically ...
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09/09/2019
Unsupervised Domain Adaptation for Depth Prediction from Images
State-of-the-art approaches to infer dense depth measurements from image...
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08/05/2019
Semi-Automatic Labeling for Deep Learning in Robotics
In this paper, we propose Augmented Reality Semi-automatic labeling (ARS...
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07/17/2019
Real-Time Highly Accurate Dense Depth on a Power Budget using an FPGA-CPU Hybrid SoC
Obtaining highly accurate depth from stereo images in real time has many...
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04/09/2019
Learning Across Tasks and Domains
Recent works have proven that many relevant visual tasks are closely rel...
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04/05/2019
Learning to Adapt for Stereo
Real world applications of stereo depth estimation require models that a...
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02/02/2019
Domain invariant hierarchical embedding for grocery products recognition
Recognizing packaged grocery products based solely on appearance is stil...
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10/29/2018
Real-Time RGB-D Camera Pose Estimation in Novel Scenes using a Relocalisation Cascade
Camera pose estimation is an important problem in computer vision. Commo...
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10/13/2018
Exploiting Semantics in Adversarial Training for Image-Level Domain Adaptation
Performance achievable by modern deep learning approaches are directly r...
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10/12/2018
Real-time self-adaptive deep stereo
Deep convolutional neural networks trained end-to-end are the undisputed...
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10/10/2018
Let's take a Walk on Superpixels Graphs: Deformable Linear Objects Segmentation and Model Estimation
While robotic manipulation of rigid objects is quite straightforward, co...
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10/09/2018
Geometry meets semantics for semi-supervised monocular depth estimation
Depth estimation from a single image represents a very exciting challeng...
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10/03/2018
A deep learning pipeline for product recognition on store shelves
Recognition of grocery products in store shelves poses peculiar challeng...
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10/03/2018
A deep learning pipeline for product recognition in store shelves
Recognition of grocery products in store shelves poses peculiar challeng...
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07/26/2017
Product recognition in store shelves as a sub-graph isomorphism problem
The arrangement of products in store shelves is carefully planned to max...
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02/09/2017
On-the-Fly Adaptation of Regression Forests for Online Camera Relocalisation
Camera relocalisation is an important problem in computer vision, with a...
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11/13/2015
