robot-learning-freiburg/MDPCalib

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robot-learning-freiburg/MDPCalib

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Automatic Target-Less Camera-LiDAR Calibration from Motion and Deep Point Correspondences

LCDNet

PyTorch code for training LCDNet for loop closure detection in LiDAR SLAM. http://rl.uni-freiburg.de/research/lidar-slam-lc

ros_sam

ROS wrapper for Meta's Segment-Anything model

CL-SLAM

Continual SLAM: Beyond Lifelong Simultaneous Localization and Mapping through Continual Learning. http://continual-slam.cs.uni-freiburg.de

PanopticBEV

Bird's-Eye-View Panoptic Segmentation Using Monocular Frontal View Images. http://panoptic-bev.cs.uni-freiburg.de

EfficientLPS

PyTorch code for training EfficientLPS for LiDAR panoptic segmentation. https://rl.uni-freiburg.de/research/lidar-panoptic

MM-DistillNet

PyTorch code for training MM-DistillNet for multimodal knowledge distillation. http://rl.uni-freiburg.de/research/multimodal-distill

PADLoC

LiDAR-Based Deep Loop Closure Detection and Registration using Panoptic Attention

CURB-SG

[ICRA 2024] Collaborative Dynamic 3D Scene Graphs for Automated Driving

mobile-rl

Learning Navigation for Arbitrary Mobile Manipulation Motions in Unseen and Dynamic Environments. http://mobile-rl.cs.uni-freiburg.de

MoMa-LLM

Language-Grounded Dynamic Scene Graphs for Interactive Object Search with Mobile Manipulation. Project website: http://moma-llm.cs.uni-freiburg.de

BEVCar

[IROS2024] Camera-Radar Fusion for BEV Map and Object Segmentation

Batch3DMOT

3D Multi-Object Tracking Using Graph Neural Networks with Cross-Edge Modality Attention. http://batch3dmot.cs.uni-freiburg.de

Panoptic-Tracking

SPINO

Few-Shot Panoptic Segmentation With Foundation Models

CoDEPS

Continual Learning for Depth Estimation and Panoptic Segmentation

SkyEye

SkyEye: Self-Supervised Bird's-Eye-View Semantic Mapping Using Monocular Frontal View Images

DynaFill

Dynamic Object Removal and Spatio-Temporal RGB-D Inpainting via Geometry-Aware Adversarial Learning

CARTO

Official Implementation of CARTO: Category and Joint Agnostic Reconstruction of ARTiculated Objects

Jupyter Notebook

kinematic-feasibility-rl

Learning Kinematic Feasibility through Reinforcement Leanring: http://rl.uni-freiburg.de/research/kinematic-feasibility-rl

RaLF

RaLF: Flow-based Global and Metric Radar Localization in LiDAR Maps

HIMOS

Learning Hierarchical Interactive Multi-Object Search for Mobile Manipulation. Project website: http://himos.cs.uni-freiburg.de

CEILing

Active-Particle-Filter-Networks

Official repository for Active Particle Filter Networks: Efficient Active Localization in Continuous Action Spaces and Large Maps

CenterGrasp

Multi-Object-Search

Learning Long-Horizon Robot Exploration Strategies for Multi-Object Search in Continuous Action Spaces. http://multi-object-search.cs.uni-freiburg.de

Dav-Nav

Catch Me If You Hear Me: Audio-Visual Navigation in Complex Unmapped Environments with Moving Sounds. http://dav-nav.cs.uni-freiburg.de

PASTEL

A Good Foundation is Worth Many Labels: Label-Efficient Panoptic Segmentation

amodal-panoptic

Semantic-Search

Perception Matters: Enhancing Embodied AI with Uncertainty-Aware Semantic Segmentation. Project Website: http://semantic-search.cs.uni-freiburg.de

Jupyter Notebook

TAPAS

PyTorch code for TAPAS-GMM.

bopt_gmm

bask

PyTorch code for Bayesian Scene Keypoints.

APSNet

rl_tasks

PAPS

INoD

INoD: Injected Noise Discriminator for Self-Supervised Representation Learning in Agricultural Fields.