Indoor-SfMLearner[ECCV'20] Patch-match and Plane-regularization for Unsupervised Indoor Depth Estimation
Stars: ✭ 115 (+475%)
learning-topology-synthetic-dataTensorflow implementation of Learning Topology from Synthetic Data for Unsupervised Depth Completion (RAL 2021 & ICRA 2021)
Stars: ✭ 22 (+10%)
NMFADMMA sparsity aware implementation of "Alternating Direction Method of Multipliers for Non-Negative Matrix Factorization with the Beta-Divergence" (ICASSP 2014).
Stars: ✭ 39 (+95%)
DE resnet unet hybDepth estimation from RGB images using fully convolutional neural networks.
Stars: ✭ 40 (+100%)
srVAEVAE with RealNVP prior and Super-Resolution VAE in PyTorch. Code release for https://arxiv.org/abs/2006.05218.
Stars: ✭ 56 (+180%)
LinearCorexFast, linear version of CorEx for covariance estimation, dimensionality reduction, and subspace clustering with very under-sampled, high-dimensional data
Stars: ✭ 39 (+95%)
SimCLR-in-TensorFlow-2(Minimally) implements SimCLR (https://arxiv.org/abs/2002.05709) in TensorFlow 2.
Stars: ✭ 75 (+275%)
KD3AHere is the official implementation of the model KD3A in paper "KD3A: Unsupervised Multi-Source Decentralized Domain Adaptation via Knowledge Distillation".
Stars: ✭ 63 (+215%)
M4DepthOfficial implementation of the network presented in the paper "M4Depth: A motion-based approach for monocular depth estimation on video sequences"
Stars: ✭ 62 (+210%)
DRNETPyTorch implementation of the NIPS 2017 paper - Unsupervised Learning of Disentangled Representations from Video
Stars: ✭ 45 (+125%)
deep learningDeep-learning approaches to object recognition from 3D data
Stars: ✭ 19 (-5%)
altairAssessing Source Code Semantic Similarity with Unsupervised Learning
Stars: ✭ 42 (+110%)
sc depth plPytorch Lightning Implementation of SC-Depth (V1, V2...) for Unsupervised Monocular Depth Estimation.
Stars: ✭ 86 (+330%)
HoHoNet"HoHoNet: 360 Indoor Holistic Understanding with Latent Horizontal Features" official pytorch implementation.
Stars: ✭ 65 (+225%)
seq2singleVisual place recognition from opposing viewpoints under extreme appearance variations
Stars: ✭ 15 (-25%)
youtokentome-rubyHigh performance unsupervised text tokenization for Ruby
Stars: ✭ 17 (-15%)
Semantic-Mono-DepthGeometry meets semantics for semi-supervised monocular depth estimation - ACCV 2018
Stars: ✭ 98 (+390%)
project-defudeRefocus an image just by clicking on it with no additional data
Stars: ✭ 69 (+245%)
dadsCode for 'Dynamics-Aware Unsupervised Discovery of Skills' (DADS). Enables skill discovery without supervision, which can be combined with model-based control.
Stars: ✭ 138 (+590%)
kmedoidsThe Partitioning Around Medoids (PAM) implementation of the K-Medoids algorithm in Python [Unmaintained]
Stars: ✭ 18 (-10%)
MVGLTCyb 2018: Graph learning for multiview clustering
Stars: ✭ 26 (+30%)
al-fk-self-supervisionOfficial PyTorch code for CVPR 2020 paper "Deep Active Learning for Biased Datasets via Fisher Kernel Self-Supervision"
Stars: ✭ 28 (+40%)
DiverseDepthThe code and data of DiverseDepth
Stars: ✭ 150 (+650%)
DiscoveryMining Discourse Markers for Unsupervised Sentence Representation Learning
Stars: ✭ 48 (+140%)
dti-sprites(ICCV 2021) Code for "Unsupervised Layered Image Decomposition into Object Prototypes" paper
Stars: ✭ 33 (+65%)
dti-clustering(NeurIPS 2020 oral) Code for "Deep Transformation-Invariant Clustering" paper
Stars: ✭ 60 (+200%)
catgan pytorchUnsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks
Stars: ✭ 50 (+150%)
Unsupervised-Learning-in-RWorkshop (6 hours): Clustering (Hdbscan, LCA, Hopach), dimension reduction (UMAP, GLRM), and anomaly detection (isolation forests).
Stars: ✭ 34 (+70%)
kwxBERT, LDA, and TFIDF based keyword extraction in Python
Stars: ✭ 33 (+65%)
Deep-Association-LearningTensorflow Implementation on Paper [BMVC2018]Deep Association Learning for Unsupervised Video Person Re-identification
Stars: ✭ 68 (+240%)
adareg-monodispnetRepository for Bilateral Cyclic Constraint and Adaptive Regularization for Unsupervised Monocular Depth Prediction (CVPR2019)
Stars: ✭ 22 (+10%)
uctfUnsupervised Controllable Text Generation (Applied to text Formalization)
Stars: ✭ 19 (-5%)
OMG Depth FusionProbabilistic depth fusion based on Optimal Mixture of Gaussians for depth cameras
Stars: ✭ 52 (+160%)
PiCIEPiCIE: Unsupervised Semantic Segmentation using Invariance and Equivariance in clustering (CVPR2021)
Stars: ✭ 102 (+410%)
Depth estimationDeep learning model to estimate the depth of image.
Stars: ✭ 62 (+210%)
spearSPEAR: Programmatically label and build training data quickly.
Stars: ✭ 81 (+305%)
ML2017FALLMachine Learning (EE 5184) in NTU
Stars: ✭ 66 (+230%)
kmeansA simple implementation of K-means (and Bisecting K-means) clustering algorithm in Python
Stars: ✭ 18 (-10%)
treecutFind nodes in hierarchical clustering that are statistically significant
Stars: ✭ 26 (+30%)
T-CorExImplementation of linear CorEx and temporal CorEx.
Stars: ✭ 31 (+55%)
PICParametric Instance Classification for Unsupervised Visual Feature Learning, NeurIPS 2020
Stars: ✭ 41 (+105%)
UEGAN[TIP2020] Pytorch implementation of "Towards Unsupervised Deep Image Enhancement with Generative Adversarial Network"
Stars: ✭ 68 (+240%)
deep-INFOMAXChainer implementation of deep-INFOMAX
Stars: ✭ 32 (+60%)
pais-mvsMulti-view stereo image-based 3D reconstruction
Stars: ✭ 55 (+175%)
back2futureUnsupervised Learning of Multi-Frame Optical Flow with Occlusions
Stars: ✭ 39 (+95%)
rectified-features[ECCV 2020] Single image depth prediction allows us to rectify planar surfaces in images and extract view-invariant local features for better feature matching
Stars: ✭ 57 (+185%)