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12/15/2022
Multi-task Fusion for Efficient Panoptic-Part Segmentation
In this paper, we introduce a novel network that generates semantic, ins...
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11/28/2022
Object Permanence in Object Detection Leveraging Temporal Priors at Inference Time
Object permanence is the concept that objects do not suddenly disappear ...
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10/13/2022
Attribution-aware Weight Transfer: A Warm-Start Initialization for Class-Incremental Semantic Segmentation
In class-incremental semantic segmentation (CISS), deep learning archite...
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06/30/2022
Self-SuperFlow: Self-supervised Scene Flow Prediction in Stereo Sequences
In recent years, deep neural networks showed their exceeding capabilitie...
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04/01/2022
RMS-FlowNet: Efficient and Robust Multi-Scale Scene Flow Estimation for Large-Scale Point Clouds
The proposed RMS-FlowNet is a novel end-to-end learning-based architectu...
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10/25/2021
Multi-scale Iterative Residuals for Fast and Scalable Stereo Matching
Despite the remarkable progress of deep learning in stereo matching, the...
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11/03/2020
A Deep Temporal Fusion Framework for Scene Flow Using a Learnable Motion Model and Occlusions
Motion estimation is one of the core challenges in computer vision. With...
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10/21/2020
MonoComb: A Sparse-to-Dense Combination Approach for Monocular Scene Flow
Contrary to the ongoing trend in automotive applications towards usage o...
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10/16/2020
HPERL: 3D Human Pose Estimation from RGB and LiDAR
In-the-wild human pose estimation has a huge potential for various field...
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08/21/2020
SSGP: Sparse Spatial Guided Propagation for Robust and Generic Interpolation
Interpolation of sparse pixel information towards a dense target resolut...
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08/18/2020
DeepLiDARFlow: A Deep Learning Architecture For Scene Flow Estimation Using Monocular Camera and Sparse LiDAR
Scene flow is the dense 3D reconstruction of motion and geometry of a sc...
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06/22/2020
ResFPN: Residual Skip Connections in Multi-Resolution Feature Pyramid Networks for Accurate Dense Pixel Matching
Dense pixel matching is required for many computer vision algorithms suc...
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10/31/2019
LiDAR-Flow: Dense Scene Flow Estimation from Sparse LiDAR and Stereo Images
We propose a new approach called LiDAR-Flow to robustly estimate a dense...
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04/12/2019
An Empirical Evaluation Study on the Training of SDC Features for Dense Pixel Matching
Training a deep neural network is a non-trivial task. Not only the tunin...
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04/12/2019
PWOC-3D: Deep Occlusion-Aware End-to-End Scene Flow Estimation
In the last few years, convolutional neural networks (CNNs) have demonst...
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04/05/2019
SDC - Stacked Dilated Convolution: A Unified Descriptor Network for Dense Matching Tasks
Dense pixel matching is important for many computer vision tasks such as...
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02/26/2019
SceneFlowFields++: Multi-frame Matching, Visibility Prediction, and Robust Interpolation for Scene Flow Estimation
State-of-the-art scene flow algorithms pursue the conflicting targets of...
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08/30/2018
Automated Scene Flow Data Generation for Training and Verification
Scene flow describes the 3D position as well as the 3D motion of each pi...
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08/30/2018
Dense Scene Flow from Stereo Disparity and Optical Flow
Scene flow describes 3D motion in a 3D scene. It can either be modeled a...
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06/20/2018
Dynamic Risk Assessment for Vehicles of Higher Automation Levels by Deep Learning
Vehicles of higher automation levels require the creation of situation a...
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05/09/2018
FlowFields++: Accurate Optical Flow Correspondences Meet Robust Interpolation
Optical Flow algorithms are of high importance for many applications. Re...
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01/15/2018
Combining Stereo Disparity and Optical Flow for Basic Scene Flow
Scene flow is a description of real world motion in 3D that contains mor...
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10/27/2017