Search Results for author: Francis Engelmann

Found 24 papers, 11 papers with code

Spot-Compose: A Framework for Open-Vocabulary Object Retrieval and Drawer Manipulation in Point Clouds

no code implementations18 Apr 2024 Oliver Lemke, Zuria Bauer, René Zurbrügg, Marc Pollefeys, Francis Engelmann, Hermann Blum

This allows for accurate detection directly in 3D scenes, object- and environment-aware grasp prediction, as well as robust and repeatable robotic manipulation.

3D Instance Segmentation Pose Estimation +3

OpenNeRF: Open Set 3D Neural Scene Segmentation with Pixel-Wise Features and Rendered Novel Views

no code implementations4 Apr 2024 Francis Engelmann, Fabian Manhardt, Michael Niemeyer, Keisuke Tateno, Marc Pollefeys, Federico Tombari

Our OpenNeRF further leverages NeRF's ability to render novel views and extract open-set VLM features from areas that are not well observed in the initial posed images.

Image Segmentation Point Cloud Segmentation +2

ICGNet: A Unified Approach for Instance-Centric Grasping

1 code implementation18 Jan 2024 René Zurbrügg, Yifan Liu, Francis Engelmann, Suryansh Kumar, Marco Hutter, Vaishakh Patil, Fisher Yu

Executing a successful grasp in a cluttered environment requires multiple levels of scene understanding: First, the robot needs to analyze the geometric properties of individual objects to find feasible grasps.

Object Object Reconstruction +1

ALSTER: A Local Spatio-Temporal Expert for Online 3D Semantic Reconstruction

no code implementations29 Nov 2023 Silvan Weder, Francis Engelmann, Johannes L. Schönberger, Akihito Seki, Marc Pollefeys, Martin R. Oswald

Using these main contributions, our method can enable scenarios with real-time constraints and can scale to arbitrary scene sizes by processing and updating the scene only in a local region defined by the new measurement.

3D Semantic Segmentation Mixed Reality

LABELMAKER: Automatic Semantic Label Generation from RGB-D Trajectories

no code implementations20 Nov 2023 Silvan Weder, Hermann Blum, Francis Engelmann, Marc Pollefeys

Semantic annotations are indispensable to train or evaluate perception models, yet very costly to acquire.

Neural Rendering

AGILE3D: Attention Guided Interactive Multi-object 3D Segmentation

no code implementations1 Jun 2023 Yuanwen Yue, Sabarinath Mahadevan, Jonas Schult, Francis Engelmann, Bastian Leibe, Konrad Schindler, Theodora Kontogianni

In an iterative process, the model assigns each data point to an object (or the background), while the user corrects errors in the resulting segmentation and feeds them back into the model.

Binary Classification Interactive Segmentation +2

Connecting the Dots: Floorplan Reconstruction Using Two-Level Queries

1 code implementation CVPR 2023 Yuanwen Yue, Theodora Kontogianni, Konrad Schindler, Francis Engelmann

Instead, we formulate floorplan reconstruction as a single-stage structured prediction task: find a variable-size set of polygons, which in turn are variable-length sequences of ordered vertices.

Structured Prediction Vocal Bursts Valence Prediction

Mask3D: Mask Transformer for 3D Semantic Instance Segmentation

1 code implementation6 Oct 2022 Jonas Schult, Francis Engelmann, Alexander Hermans, Or Litany, Siyu Tang, Bastian Leibe

Modern 3D semantic instance segmentation approaches predominantly rely on specialized voting mechanisms followed by carefully designed geometric clustering techniques.

3D Instance Segmentation 3D Semantic Instance Segmentation +1

4D-StOP: Panoptic Segmentation of 4D LiDAR using Spatio-temporal Object Proposal Generation and Aggregation

1 code implementation29 Sep 2022 Lars Kreuzberg, Idil Esen Zulfikar, Sabarinath Mahadevan, Francis Engelmann, Bastian Leibe

Our voting-based tracklet generation method followed by geometric feature-based aggregation generates significantly improved panoptic LiDAR segmentation quality when compared to modeling the entire 4D volume using Gaussian probability distributions.

4D Panoptic Segmentation Object Proposal Generation +1

Mix3D: Out-of-Context Data Augmentation for 3D Scenes

3 code implementations5 Oct 2021 Alexey Nekrasov, Jonas Schult, Or Litany, Bastian Leibe, Francis Engelmann

Since scene context helps reasoning about object semantics, current works focus on models with large capacity and receptive fields that can fully capture the global context of an input 3D scene.

3D Semantic Segmentation

3D-MPA: Multi-Proposal Aggregation for 3D Semantic Instance Segmentation

1 code implementation CVPR 2020 Francis Engelmann, Martin Bokeloh, Alireza Fathi, Bastian Leibe, Matthias Niessner

We show that grouping proposals improves over NMS and outperforms previous state-of-the-art methods on the tasks of 3D object detection and semantic instance segmentation on the ScanNetV2 benchmark and the S3DIS dataset.

3D Object Detection 3D Semantic Instance Segmentation +3

SAMP: Shape and Motion Priors for 4D Vehicle Reconstruction

1 code implementation2 May 2020 Francis Engelmann, Jörg Stückler, Bastian Leibe

In this paper, we propose to use 3D shape and motion priors to regularize the estimation of the trajectory and the shape of vehicles in sequences of stereo images.

Pose Estimation

3D-MPA: Multi Proposal Aggregation for 3D Semantic Instance Segmentation

1 code implementation30 Mar 2020 Francis Engelmann, Martin Bokeloh, Alireza Fathi, Bastian Leibe, Matthias Nießner

We show that grouping proposals improves over NMS and outperforms previous state-of-the-art methods on the tasks of 3D object detection and semantic instance segmentation on the ScanNetV2 benchmark and the S3DIS dataset.

3D Instance Segmentation 3D Object Detection +3

Dilated Point Convolutions: On the Receptive Field Size of Point Convolutions on 3D Point Clouds

1 code implementation28 Jul 2019 Francis Engelmann, Theodora Kontogianni, Bastian Leibe

In a thorough ablation study, we show that the receptive field size is directly related to the performance of 3D point cloud processing tasks, including semantic segmentation and object classification.

3D Semantic Segmentation

Know What Your Neighbors Do: 3D Semantic Segmentation of Point Clouds

no code implementations2 Oct 2018 Francis Engelmann, Theodora Kontogianni, Jonas Schult, Bastian Leibe

In this paper, we present a deep learning architecture which addresses the problem of 3D semantic segmentation of unstructured point clouds.

3D Semantic Segmentation Segmentation

Exploring Spatial Context for 3D Semantic Segmentation of Point Clouds

1 code implementation5 Feb 2018 Francis Engelmann, Theodora Kontogianni, Alexander Hermans, Bastian Leibe

The recently proposed PointNet architecture presents an interesting step ahead in that it can operate on unstructured point clouds, achieving encouraging segmentation results.

3D Semantic Segmentation Segmentation

Keyframe-Based Visual-Inertial Online SLAM with Relocalization

no code implementations7 Feb 2017 Anton Kasyanov, Francis Engelmann, Jörg Stückler, Bastian Leibe

Our visual-inertial SLAM system is based on a real-time capable visual-inertial odometry method that provides locally consistent trajectory and map estimates.

Pose Tracking Simultaneous Localization and Mapping

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