Label ToolWeb application for image labeling and segmentation
DeepresearchThis repository is the collection of research papers in Deep learning, computer vision and NLP.
PointnetvladPointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition, CVPR 2018
FaceimagequalityCode and information for face image quality assessment with SER-FIQ
Superpixels RevisitedLibrary containing 7 state-of-the-art superpixel algorithms with a total of 9 implementations used for evaluation purposes in [1] utilizing an extended version of the Berkeley Segmentation Benchmark.
Arc Robot VisionMIT-Princeton Vision Toolbox for Robotic Pick-and-Place at the Amazon Robotics Challenge 2017 - Robotic Grasping and One-shot Recognition of Novel Objects with Deep Learning.
Triplet AttentionOfficial PyTorch Implementation for "Rotate to Attend: Convolutional Triplet Attention Module." [WACV 2021]
Staple[CVPR'16] Staple: Complementary Learners for Real-Time Tracking"
OpenvheadA 3D virtual head control system for VTuber in Unity with smooth motion and robust facial expressions
GipumaMassively Parallel Multiview Stereopsis by Surface Normal Diffusion
Pytorch cifar10Pretrained TorchVision models on CIFAR10 dataset (with weights)
Aidl kbA Knowledge Base for the FB Group Artificial Intelligence and Deep Learning (AIDL)
IhogVisualizing Object Detection Features. ICCV 2013
3dmmasstnMatConvNet implementation for incorporating a 3D Morphable Model (3DMM) into a Spatial Transformer Network (STN)
Graph Cut RansacThe Graph-Cut RANSAC algorithm proposed in paper: Daniel Barath and Jiri Matas; Graph-Cut RANSAC, Conference on Computer Vision and Pattern Recognition, 2018. It is available at http://openaccess.thecvf.com/content_cvpr_2018/papers/Barath_Graph-Cut_RANSAC_CVPR_2018_paper.pdf
RiglEnd-to-end training of sparse deep neural networks with little-to-no performance loss.
Visdial[CVPR 2017] Torch code for Visual Dialog
BvQuickly view satellite imagery, hyperspectral imagery, and machine learning image outputs directly in your iTerm2 terminal.
Ava downloader⏬ Download AVA dataset (A Large-Scale Database for Aesthetic Visual Analysis)
Scancomplete[CVPR'18] ScanComplete: Large-Scale Scene Completion and Semantic Segmentation for 3D Scans
MarvinjJavascript Image Processing Framework based on Marvin Framework
PclpyPython bindings for the Point Cloud Library (PCL)
ImageComputer Vision and Image Recognition algorithms for R users
Transfer Learning SuiteTransfer Learning Suite in Keras. Perform transfer learning using any built-in Keras image classification model easily!
PynetGenerating RGB photos from RAW image files with PyNET
LuminothDeep Learning toolkit for Computer Vision.
FcnChainer Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)
Binary Human Pose EstimationThis code implements a demo of the Binarized Convolutional Landmark Localizers for Human Pose Estimation and Face Alignment with Limited Resources paper by Adrian Bulat and Georgios Tzimiropoulos.
PydltPyTorch based Deep Learning Toolbox
Highres NetPytorch implementation of HighRes-net, a neural network for multi-frame super-resolution, trained and tested on the European Space Agency’s Kelvin competition.
MolaA Modular Optimization framework for Localization and mApping (MOLA)
Deep Iterative CollaborationPytorch implementation of Deep Face Super-Resolution with Iterative Collaboration between Attentive Recovery and Landmark Estimation (CVPR 2020)
GyroflowVideo stabilization using gyro data from GoPro or external logs
Guided Attention Inference NetworkContains implementation of Guided Attention Inference Network (GAIN) presented in Tell Me Where to Look(CVPR 2018). This repository aims to apply GAIN on fcn8 architecture used for segmentation.
PapersSummaries of machine learning papers
Semantic Segmentation SuiteSemantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!
SwapnetVirtual Clothing Try-on with Deep Learning. PyTorch reproduction of SwapNet by Raj et al. 2018. Now with Docker support!