154 citations · 243 across the 27 of their papers we have counts for
20 papers · 1 filter
OpenCVL: An Open, Diverse, and Large-Scale Dataset for Fine-Grained Cross-View Localization
Zimin Xia, Mubariz Zaffar, Junsheng Fu +2
Fine-grained Cross-View Localization (CVL) estimates the precise position and orientation of a ground-level image by aligning it with geo-referenced aerial imagery, offering a scal…
RVLoss: Runoff Vote Loss for Self-Supervised LiDAR Scene Flow Estimation
Shiming Wang, Liangliang Nan, Julian Kooij +2
LiDAR scene flow estimates point-wise motion between two consecutive scans, referred to as the source and target. Leading self-supervised methods typically minimize the Chamfer los…
Emergent 3D Instance Segmentation from Self-Supervised Point Transformers
Ted Lentsch, Santiago Montiel-Marín, Holger Caesar +1
Unsupervised 3D instance segmentation of outdoor LiDAR scans has traditionally relied on handcrafted geometric priors such as density-based clustering, motion cues, or projected 2D…
AsyncBEV: Cross-modal Flow Alignment in Asynchronous 3D Object Detection
Shiming Wang, Holger Caesar, Liangliang Nan +1
In autonomous driving, multi-modal perception tasks like 3D object detection typically rely on well-synchronized sensors, both at training and inference. However, despite the use o…
The Overlooked Value of Test-time Reference Sets in Visual Place Recognition
Mubariz Zaffar, Liangliang Nan, Sebastian Scherer +1
Given a query image, Visual Place Recognition (VPR) is the task of retrieving an image of the same place from a reference database with robustness to viewpoint and appearance chang…
NeuSEditor: From Multi-View Images to Text-Guided Neural Surface Edits
Nail Ibrahimli, Julian F. P. Kooij, Liangliang Nan
Implicit surface representations are valued for their compactness and continuity, but they pose significant challenges for editing. Despite recent advancements, existing methods of…
VoteFlow: Enforcing Local Rigidity in Self-Supervised Scene Flow
Yancong Lin, Shiming Wang, Liangliang Nan +2
Scene flow estimation aims to recover per-point motion from two adjacent LiDAR scans. However, in real-world applications such as autonomous driving, points rarely move independent…
Adapting Fine-Grained Cross-View Localization to Areas without Fine Ground Truth
Zimin Xia, Yujiao Shi, Hongdong Li +1
Given a ground-level query image and a geo-referenced aerial image that covers the query's local surroundings, fine-grained cross-view localization aims to estimate the location of…
On the Estimation of Image-matching Uncertainty in Visual Place Recognition
Mubariz Zaffar, Liangliang Nan, Julian F. P. Kooij
In Visual Place Recognition (VPR) the pose of a query image is estimated by comparing the image to a map of reference images with known reference poses. As is typical for image ret…
MuVieCAST: Multi-View Consistent Artistic Style Transfer
Nail Ibrahimli, Julian F. P. Kooij, Liangliang Nan
We introduce MuVieCAST, a modular multi-view consistent style transfer network architecture that enables consistent style transfer between multiple viewpoints of the same scene. Th…
UniBEV: Multi-modal 3D Object Detection with Uniform BEV Encoders for Robustness against Missing Sensor Modalities
Shiming Wang, Holger Caesar, Liangliang Nan +1
Multi-sensor object detection is an active research topic in automated driving, but the robustness of such detection models against missing sensor input (modality missing), e.g., d…
CoPR: Towards Accurate Visual Localization With Continuous Place-descriptor Regression
Mubariz Zaffar, Liangliang Nan, Julian Francisco Pieter Kooij
Visual Place Recognition (VPR) is an image-based localization method that estimates the camera location of a query image by retrieving the most similar reference image from a map o…
Convolutional Cross-View Pose Estimation
Zimin Xia, Olaf Booij, Julian F. P. Kooij
We propose a novel end-to-end method for cross-view pose estimation. Given a ground-level query image and an aerial image that covers the query's local neighborhood, the 3 Degrees-…
Push-the-Boundary: Boundary-aware Feature Propagation for Semantic Segmentation of 3D Point Clouds
Shenglan Du, Nail Ibrahimli, Jantien Stoter +2
Feedforward fully convolutional neural networks currently dominate in semantic segmentation of 3D point clouds. Despite their great success, they suffer from the loss of local info…
How do Cross-View and Cross-Modal Alignment Affect Representations in Contrastive Learning?
Thomas M. Hehn, Julian F. P. Kooij, Dariu M. Gavrila
Various state-of-the-art self-supervised visual representation learning approaches take advantage of data from multiple sensors by aligning the feature representations across views…
SliceMatch: Geometry-guided Aggregation for Cross-View Pose Estimation
Ted Lentsch, Zimin Xia, Holger Caesar +1
This work addresses cross-view camera pose estimation, i.e., determining the 3-Degrees-of-Freedom camera pose of a given ground-level image w.r.t. an aerial image of the local area…
Visual Cross-View Metric Localization with Dense Uncertainty Estimates
Zimin Xia, Olaf Booij, Marco Manfredi +1
This work addresses visual cross-view metric localization for outdoor robotics. Given a ground-level color image and a satellite patch that contains the local surroundings, the tas…
DDL-MVS: Depth Discontinuity Learning for MVS Networks
Nail Ibrahimli, Hugo Ledoux, Julian Kooij +1
Traditional MVS methods have good accuracy but struggle with completeness, while recently developed learning-based multi-view stereo (MVS) techniques have improved completeness exc…
CNN based Road User Detection using the 3D Radar Cube
Andras Palffy, Jiaao Dong, Julian F. P. Kooij +1
This letter presents a novel radar based, single-frame, multi-class detection method for moving road users (pedestrian, cyclist, car), which utilizes low-level radar cube data. The…
Cross-Modal Distillation for RGB-Depth Person Re-Identification
Frank Hafner, Amran Bhuiyan, Julian F. P. Kooij +1
Person re-identification is a key challenge for surveillance across multiple sensors. Prompted by the advent of powerful deep learning models for visual recognition, and inexpensiv…