robot-learning-freiburg Goto Github PK

active-particle-filter-networks

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

adapnet

TensorFlow model for training AdapNet for semantic segmentation

adapnet-pp

TensorFlow model for training AdapNet++ for semantic segmentation

adaptlps

amodal-optical-flow

Official implementation for "Amodal Optical Flow" (ICRA 2024).

amodal-panoptic

apsnet

bask

PyTorch code for Bayesian Scene Keypoints.

batch3dmot

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

bevcar

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

bopt_gmm

carto

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

ceiling

centergrasp

cl-slam

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

cmode

TensorFlow model for training CMoDE for multimodal semantic segmentation

codeps

Continual Learning for Depth Estimation and Panoptic Segmentation

curb-sg

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

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

dynafill

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

efficientlps

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

efficientps

PyTorch code for training EfficientPS for Panoptic Segmentation of images. https://rl.uni-freiburg.de/research/panoptic

himos

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

hov-sg

[RSS2024] HOV-SG: Hierarchical Open-Vocabulary 3D Scene Graphs for Language-Grounded Robot Navigation"

inod

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

kinematic-feasibility-rl

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

lcdnet

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

mdpcalib

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

mm-distillnet

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

mobile-rl

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