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sarsigmadelta's Projects

ik icon ik

Minimal Inverse Kinematics library

image_segmentation icon image_segmentation

Pytorch implementation of U-Net, R2U-Net, Attention U-Net, and Attention R2U-Net.

ipman-r icon ipman-r

This is a code repository for training the IPMAN-R model and evaluating performance

jetbot-ros2 icon jetbot-ros2

ROS 2 implementation of a Teleoperated robot with live video feed using webrtc and SLAM using realsense's stereocameras. Running on a Jetson Nano

kairos_minerl_basalt icon kairos_minerl_basalt

Codebase for the solution that won first place and was awarded the most human-like agent in the 2021 NeurIPS Competition MineRL BASALT Challenge.

kandinsky-2 icon kandinsky-2

Kandinsky 2 — multilingual text2image latent diffusion model

keras-yolo2 icon keras-yolo2

Easy training on custom dataset. Various backends (MobileNet and SqueezeNet) supported. A YOLO demo to detect raccoon run entirely in brower is accessible at https://git.io/vF7vI (not on Windows).

learn-webgl icon learn-webgl

This repo contains the code used in the Learn WebGL series on the Invent Box Youtube channel.

libsgm icon libsgm

Stereo Semi Global Matching by cuda

metrabs icon metrabs

This is a computer vision algorithm that takes a single RGB image as the input and estimates 3D human poses as the output.

minimal-ik icon minimal-ik

Solving SMPL/MANO parameters from keypoint coordinates.

mmaction icon mmaction

An open-source toolbox for action understanding based on PyTorch

mmaction2 icon mmaction2

OpenMMLab's Next Generation Action Understanding Toolbox and Benchmark

mocapnet icon mocapnet

We present MocapNET2, a real-time method that estimates the 3D human pose directly in the popular Bio Vision Hierarchy (BVH) format, given estimations of the 2D body joints originating from monocular color images. Our contributions include: (a) A novel and compact 2D pose NSRM representation. (b) A human body orientation classifier and an ensemble of orientation-tuned neural networks that regress the 3D human pose by also allowing for the decomposition of the body to an upper and lower kinematic hierarchy. This permits the recovery of the human pose even in the case of significant occlusions. (c) An efficient Inverse Kinematics solver that refines the neural-network-based solution providing 3D human pose estimations that are consistent with the limb sizes of a target person (if known). All the above yield a 33% accuracy improvement on the Human 3.6 Million (H3.6M) dataset compared to the baseline method (MocapNET) while maintaining real-time performance (70 fps in CPU-only execution).

monocular-visual-odometry icon monocular-visual-odometry

A simple monocular visual odometry (part of vSLAM) by ORB keypoints with initialization, tracking, local map and bundle adjustment. (WARNING: Hi, I'm sorry that this project is tuned for course demo, not for real world applications !!!)

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