Achuthankrishna

Achuthankrishna's Stars

• Avik-Jain/100-Days-Of-ML-Code

  100 Days of ML Coding

  45.5k2.4k010.6k

• IDEA-Research/Grounded-Segment-Anything

  Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything

  Language:Jupyter Notebook15.2k1143881.4k

• raulmur/ORB_SLAM2

  Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalization Capabilities

  Language:C++9.4k3729674.7k

• johnBuffer/AntSimulator

  Simple Ants simulator

  Language:C++2.2k5742282

• black0017/MedicalZooPytorch

  A pytorch-based deep learning framework for multi-modal 2D/3D medical image segmentation

  Language:Python1.7k3525299

• chvmp/champ

  MIT Cheetah I Implementation

  Language:C++1.6k62121360

• StanfordASL/Trajectron-plus-plus

  Code accompanying the ECCV 2020 paper "Trajectron++: Dynamically-Feasible Trajectory Forecasting With Heterogeneous Data" by Tim Salzmann*, Boris Ivanovic*, Punarjay Chakravarty, and Marco Pavone (* denotes equal contribution).

  Language:Jupyter Notebook6602491188

• eleurent/rl-agents

  Implementations of Reinforcement Learning and Planning algorithms

  Language:Python58919101153

• sea-bass/turtlebot3_behavior_demos

  Example repository for autonomous behaviors using TurtleBot3, as well as Docker workflows in ROS based projects.

  Language:Python28783255

• mp2893/medgan

  Generative adversarial network for generating electronic health records.

  Language:Python270142189

• MoonBlvd/tad-IROS2019

  Code of the Unsupervised Traffic Accident Detection paper in Pytorch.

  Language:Python16654839

• ignc-research/arena-rosnav

  Language:Python14241254

• ros-controls/gz_ros2_control

  Connect the latest version of Gazebo with ros2_control.

  Language:C++117139986

• umautobots/bidirection-trajectory-predicter

  The code for Bi-directional Trajectory Prediction (BiTraP).

  Language:Python8052022

• ignc-research/arena-rosnav-3D

  Language:Python5881814

• vita-epfl/bounding-box-prediction

  Bounding box prediction library. Official implementation of two papers on human 2D/3D bounding box prediction

  Language:Python4851514

• mjpramirez/Volvo-DataX

  Language:PureBasic332615

• snmnmin12/ekf-slam

  extended kalman filter slam demo

  Language:C++302111

• bodokaiser/mrtoct-tensorflow

  Tensorflow models for MRI to CT synthesis.

  Language:Jupyter Notebook264155

• lucasrm25/Probabilistic-Machine-Learning

  Repository for the course Probabilistic Machine Learning at Tübingen University

  Language:Jupyter Notebook223011

• johnBuffer/Swarm

  Multithreading library

  Language:C++21402

• maxjiang93/SDFGAN

  3D Signed Distance Function Based Generative Adversarial Networks

  Language:Python14612

• VRU-intention/casr

  Intention Recognition of Pedestrians and Cyclists by 2D Pose Estimation

  Language:Python14226

• dahhmani/Motion-Planning-for-Self-Driving-Cars

  ENPM661 Planning for Autonomous Robots

  Language:Python11205

• sohiniroych/Volvo-DataX

  Language:Jupyter Notebook8305

• kyuhyong/ORB_SLAM2

  Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalization Capabilities

  Language:C++3001

• VaidehiSom/Dynamic_Obstacle_Avoidance_Using_LSTM

  We have compared 4 models- Vanilla LSTM, Social LSTM, OLSTM, and GRU to show their comparison for predicting non linear trajectories of pedestrians in different scenes. We demonstrate their performance on publically available datasets. We show how it is important to take into account the surroundings of the pedestrians to have a better accuracy

  Language:Jupyter Notebook3000