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04/06/2023
SALUDA: Surface-based Automotive Lidar Unsupervised Domain Adaptation
Learning models on one labeled dataset that generalize well on another d...
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01/24/2023
RangeViT: Towards Vision Transformers for 3D Semantic Segmentation in Autonomous Driving
Casting semantic segmentation of outdoor LiDAR point clouds as a 2D prob...
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01/24/2023
Using a Waffle Iron for Automotive Point Cloud Semantic Segmentation
Semantic segmentation of point clouds in autonomous driving datasets req...
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12/12/2022
ALSO: Automotive Lidar Self-supervision by Occupancy estimation
We propose a new self-supervised method for pre-training the backbone of...
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04/14/2022
CroCo: Cross-Modal Contrastive learning for localization of Earth Observation data
It is of interest to localize a ground-based LiDAR point cloud on remote...
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03/30/2022
Image-to-Lidar Self-Supervised Distillation for Autonomous Driving Data
Segmenting or detecting objects in sparse Lidar point clouds are two imp...
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02/03/2022
Deep Surface Reconstruction from Point Clouds with Visibility Information
Most current neural networks for reconstructing surfaces from point clou...
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01/05/2022
POCO: Point Convolution for Surface Reconstruction
Implicit neural networks have been successfully used for surface reconst...
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12/31/2021
Weakly Supervised Change Detection Using Guided Anisotropic Difusion
Large scale datasets created from crowdsourced labels or openly availabl...
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11/30/2021
NeeDrop: Self-supervised Shape Representation from Sparse Point Clouds using Needle Dropping
There has been recently a growing interest for implicit shape representa...
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10/04/2021
PCAM: Product of Cross-Attention Matrices for Rigid Registration of Point Clouds
Rigid registration of point clouds with partial overlaps is a longstandi...
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08/13/2021
Generative Zero-Shot Learning for Semantic Segmentation of 3D Point Cloud
While there has been a number of studies on Zero-Shot Learning (ZSL) for...
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10/15/2020
Semi-Supervised Semantic Segmentation in Earth Observation: The MiniFrance Suite, Dataset Analysis and Multi-task Network Study
The development of semi-supervised learning techniques is essential to e...
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07/22/2020
FLOT: Scene Flow on Point Clouds Guided by Optimal Transport
We propose and study a method called FLOT that estimates scene flow on p...
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07/10/2020
STaRFlow: A SpatioTemporal Recurrent Cell for Lightweight Multi-Frame Optical Flow Estimation
We present a new lightweight CNN-based algorithm for multi-frame optical...
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04/09/2020
LightConvPoint: convolution for points
Recent state-of-the-art methods for point cloud semantic segmentation ar...
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11/04/2019
Technical Report: Co-learning of geometry and semantics for online 3D mapping
This paper is a technical report about our submission for the ECCV 2018 ...
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11/01/2019
Surface Reconstruction from 3D Line Segments
In man-made environments such as indoor scenes, when point-based 3D reco...
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09/04/2019
Distance transform regression for spatially-aware deep semantic segmentation
Understanding visual scenes relies more and more on dense pixel-wise cla...
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04/17/2019
Guided Anisotropic Diffusion and Iterative Learning for Weakly Supervised Change Detection
Large scale datasets created from user labels or openly available data h...
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04/04/2019
Generalizing discrete convolutions for unstructured point clouds
Point clouds are unstructured and unordered data, as opposed to images. ...
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10/19/2018
Urban Change Detection for Multispectral Earth Observation Using Convolutional Neural Networks
The Copernicus Sentinel-2 program now provides multispectral images at a...
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10/19/2018
Fully Convolutional Siamese Networks for Change Detection
This paper presents three fully convolutional neural network architectur...
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10/19/2018
High Resolution Semantic Change Detection
Change detection is one of the main problems in remote sensing, and is e...
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02/28/2017