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tskarthikeyann's Projects

2d-and-3d-face-alignment icon 2d-and-3d-face-alignment

This repository implements a demo of the networks described in "How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks)" paper.

3dinn icon 3dinn

Single Image 3D Interpreter Network

3dmppe_rootnet_release icon 3dmppe_rootnet_release

Official PyTorch implementation of "Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image", ICCV 2019

adience_align icon adience_align

This project provides alignment tools for faces, to be used as a preprocessing step before computer vision tasks on face images

aeron icon aeron

Efficient reliable UDP unicast, UDP multicast, and IPC message transport

autoportraitmatting icon autoportraitmatting

Tensorflow implementation of Automatic Portrait Matting on paper "Automatic Portrait Segmentation for Image Stylization"

awesome-nlp icon awesome-nlp

A curated list of resources dedicated to Natural Language Processing

bitbucket-backup icon bitbucket-backup

A python script that will backup all your bitbucket repos locally (both git and mercurial)

caffe icon caffe

Caffe: a fast open framework for deep learning.

clmtrackr icon clmtrackr

Javascript library for precise tracking of facial features via Constrained Local Models

cnn_face_detection icon cnn_face_detection

Implementation based on the paper Li et al., “A Convolutional Neural Network Cascade for Face Detection, ” 2015 CVPR

code icon code

Code for the book "Mastering OpenCV with Practical Computer Vision Projects" by Packt Publishing 2012.

compactcnncascade icon compactcnncascade

A binary library for fast and robust detection of simple objects using compact CNNs.

cp-vton icon cp-vton

Reimplemented code for "Toward Characteristic-Preserving Image-based Virtual Try-On Network"

cryptofeed icon cryptofeed

Cryptocurrency Exchange Websocket Data Feed Handler

cycle-gan-tf icon cycle-gan-tf

Reimplementation of cycle-gan(https://arxiv.org/pdf/1703.10593.pdf) with improved w-gan(https://arxiv.org/abs/1704.00028) loss in tensorflow.

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