109 Repositories
Python sparse-rf Libraries
Focal Sparse Convolutional Networks for 3D Object Detection (CVPR 2022, Oral)
Focal Sparse Convolutional Networks for 3D Object Detection (CVPR 2022, Oral) This is the official implementation of Focals Conv (CVPR 2022), a new sp
Implementation of CVPR'2022:Reconstructing Surfaces for Sparse Point Clouds with On-Surface Priors
Reconstructing Surfaces for Sparse Point Clouds with On-Surface Priors (CVPR 2022) Personal Web Pages | Paper | Project Page This repository contains
SparseInst: Sparse Instance Activation for Real-Time Instance Segmentation, CVPR 2022
SparseInst 🚀 A simple framework for real-time instance segmentation, CVPR 2022 by Tianheng Cheng, Xinggang Wang†, Shaoyu Chen, Wenqiang Zhang, Qian Z
[CVPR 2022] Structured Sparse R-CNN for Direct Scene Graph Generation
Structured Sparse R-CNN for Direct Scene Graph Generation Our paper Structured Sparse R-CNN for Direct Scene Graph Generation has been accepted by CVP
The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training
[ICLR 2022] The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training The Unreasonable Effectiveness of
Framework for Spectral Clustering on the Sparse Coefficients of Learned Dictionaries
Dictionary Learning for Clustering on Hyperspectral Images Overview Framework for Spectral Clustering on the Sparse Coefficients of Learned Dictionari
SPLADE: Sparse Lexical and Expansion Model for First Stage Ranking
SPLADE 🍴 + 🥄 = 🔎 This repository contains the weights for four models as well as the code for running inference for our two papers: [v1]: SPLADE: S
Near-Optimal Sparse Allreduce for Distributed Deep Learning (published in PPoPP'22)
Near-Optimal Sparse Allreduce for Distributed Deep Learning (published in PPoPP'22) Ok-Topk is a scheme for distributed training with sparse gradients
Very large and sparse networks appear often in the wild and present unique algorithmic opportunities and challenges for the practitioner
Sparse network learning with snlpy Very large and sparse networks appear often in the wild and present unique algorithmic opportunities and challenges
Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models
Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models Abstract Many applications of generative models rely on the marginali
Sdf sparse conv - Deep Learning on SDF for Classifying Brain Biomarkers
Deep Learning on SDF for Classifying Brain Biomarkers To reproduce the results f
Peek-a-Boo: What (More) is Disguised in a Randomly Weighted Neural Network, and How to Find It Efficiently
Peek-a-Boo: What (More) is Disguised in a Randomly Weighted Neural Network, and How to Find It Efficiently This repository is the official implementat
Official implementation of Sparse Transformer-based Action Recognition
STAR Official implementation of S parse T ransformer-based A ction R ecognition Dataset download NTU RGB+D 60 action recognition of 2D/3D skeleton fro
Scaling Vision with Sparse Mixture of Experts
Scaling Vision with Sparse Mixture of Experts This repository contains the code for training and fine-tuning Sparse MoE models for vision (V-MoE) on I
Dictionary Learning with Uniform Sparse Representations for Anomaly Detection
Dictionary Learning with Uniform Sparse Representations for Anomaly Detection Implementation of the Uniform DL Representation for AD algorithm describ
Neural network pruning for finding a sparse computational model for controlling a biological motor task.
MothPruning Scientific Overview Originally inspired by biological nervous systems, deep neural networks (DNNs) are powerful computational tools for mo
Learning with Noisy Labels via Sparse Regularization, ICCV2021
Learning with Noisy Labels via Sparse Regularization This repository is the official implementation of [Learning with Noisy Labels via Sparse Regulari
Custom studies about block sparse attention.
Block Sparse Attention 研究总结 本人近半年来对Block Sparse Attention(块稀疏注意力)的研究总结(持续更新中)。按时间顺序,主要分为如下三部分: PyTorch 自定义 CUDA 算子——以矩阵乘法为例 基于 Triton 的 Block Sparse A
Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm
Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetu
Sparse-dense operators implementation for Paddle
Sparse-dense operators implementation for Paddle This module implements coo, csc and csr matrix formats and their inter-ops with dense matrices. Feel
This repository contains the code needed to train Mega-NeRF models and generate the sparse voxel octrees
Mega-NeRF This repository contains the code needed to train Mega-NeRF models and generate the sparse voxel octrees used by the Mega-NeRF-Dynamic viewe
A 3D sparse LBM solver implemented using Taichi
taichi_LBM3D Background Taichi_LBM3D is a 3D lattice Boltzmann solver with Multi-Relaxation-Time collision scheme and sparse storage structure impleme
Dynamics-aware Adversarial Attack of 3D Sparse Convolution Network
Leaded Gradient Method (LGM) This repository contains the PyTorch implementation for paper Dynamics-aware Adversarial Attack of 3D Sparse Convolution
Open source code for the paper of Neural Sparse Voxel Fields.
Neural Sparse Voxel Fields (NSVF) Project Page | Video | Paper | Data Photo-realistic free-viewpoint rendering of real-world scenes using classical co
[AAAI 2021] EMLight: Lighting Estimation via Spherical Distribution Approximation and [ICCV 2021] Sparse Needlets for Lighting Estimation with Spherical Transport Loss
EMLight: Lighting Estimation via Spherical Distribution Approximation (AAAI 2021) Update 12/2021: We release our Virtual Object Relighting (VOR) Datas
Sinkhorn Transformer - Practical implementation of Sparse Sinkhorn Attention
Sinkhorn Transformer This is a reproduction of the work outlined in Sparse Sinkhorn Attention, with additional enhancements. It includes a parameteriz
The entmax mapping and its loss, a family of sparse softmax alternatives.
entmax This package provides a pytorch implementation of entmax and entmax losses: a sparse family of probability mappings and corresponding loss func
Examples of using sparse attention, as in "Generating Long Sequences with Sparse Transformers"
Status: Archive (code is provided as-is, no updates expected) Update August 2020: For an example repository that achieves state-of-the-art modeling pe
Sparse Physics-based and Interpretable Neural Networks
Sparse Physics-based and Interpretable Neural Networks for PDEs This repository contains the code and manuscript for research done on Sparse Physics-b
[AAAI 2022] Sparse Structure Learning via Graph Neural Networks for Inductive Document Classification
Sparse Structure Learning via Graph Neural Networks for inductive document classification Make graph dataset create co-occurrence graph for datasets.
Paper and Codes for “Embracing Single Stride 3D Object Detector with Sparse Transformer”
SST: Single-stride Sparse Transformer This is the official implementation of paper: Embracing Single Stride 3D Object Detector with Sparse Transformer
MinkLoc3D-SI: 3D LiDAR place recognition with sparse convolutions,spherical coordinates, and intensity
MinkLoc3D-SI: 3D LiDAR place recognition with sparse convolutions,spherical coordinates, and intensity Introduction The 3D LiDAR place recognition aim
Embracing Single Stride 3D Object Detector with Sparse Transformer
SST: Single-stride Sparse Transformer This is the official implementation of paper: Embracing Single Stride 3D Object Detector with Sparse Transformer
i-SpaSP: Structured Neural Pruning via Sparse Signal Recovery
i-SpaSP: Structured Neural Pruning via Sparse Signal Recovery This is a public code repository for the publication: i-SpaSP: Structured Neural Pruning
SHRIMP: Sparser Random Feature Models via Iterative Magnitude Pruning
SHRIMP: Sparser Random Feature Models via Iterative Magnitude Pruning This repository is the official implementation of "SHRIMP: Sparser Random Featur
Reviatalizing Optimization for 3D Human Pose and Shape Estimation: A Sparse Constrained Formulation
Reviatalizing Optimization for 3D Human Pose and Shape Estimation: A Sparse Constrained Formulation This is the implementation of the approach describ
A prototype COG-based tile server for sparse Mars datasets
Mars tiler Mars Tiler is a prototype web application that serves tiles from cloud-optimized GeoTIFFs, with an emphasis on supporting planetary dataset
A simple algorithm for extracting tree height in sparse scene from point cloud data.
TREE HEIGHT EXTRACTION IN SPARSE SCENES BASED ON UAV REMOTE SENSING This is the offical python implementation of the paper "Tree Height Extraction in
Codes and models of NeurIPS2021 paper - DominoSearch: Find layer-wise fine-grained N:M sparse schemes from dense neural networks
DominoSearch This is repository for codes and models of NeurIPS2021 paper - DominoSearch: Find layer-wise fine-grained N:M sparse schemes from dense n
Official implementation of the NeurIPS 2021 paper Online Learning Of Neural Computations From Sparse Temporal Feedback
Online Learning Of Neural Computations From Sparse Temporal Feedback This repository is the official implementation of the NeurIPS 2021 paper Online L
Codes of the paper Deformable Butterfly: A Highly Structured and Sparse Linear Transform.
Deformable Butterfly: A Highly Structured and Sparse Linear Transform DeBut Advantages DeBut generalizes the square power of two butterfly factor matr
PyTorch Implementation of Sparse DETR
Sparse DETR By Byungseok Roh*, Jaewoong Shin*, Wuhyun Shin*, and Saehoon Kim at Kakao Brain. (*: Equal contribution) This repository is an official im
Semi-supervised Implicit Scene Completion from Sparse LiDAR
Semi-supervised Implicit Scene Completion from Sparse LiDAR Paper Created by Pengfei Li, Yongliang Shi, Tianyu Liu, Hao Zhao, Guyue Zhou and YA-QIN ZH
Pyserini is a Python toolkit for reproducible information retrieval research with sparse and dense representations.
Pyserini Pyserini is a Python toolkit for reproducible information retrieval research with sparse and dense representations. Retrieval using sparse re
Semi-supervised Implicit Scene Completion from Sparse LiDAR
Semi-supervised Implicit Scene Completion from Sparse LiDAR Paper Created by Pengfei Li, Yongliang Shi, Tianyu Liu, Hao Zhao, Guyue Zhou and YA-QIN ZH
Spatial Sparse Convolution Library
SpConv: Spatially Sparse Convolution Library PyPI Install Downloads CPU (Linux Only) pip install spconv CUDA 10.2 pip install spconv-cu102 CUDA 11.1 p
Hidden-Fold Networks (HFN): Random Recurrent Residuals Using Sparse Supermasks
Hidden-Fold Networks (HFN): Random Recurrent Residuals Using Sparse Supermasks by Ángel López García-Arias, Masanori Hashimoto, Masato Motomura, and J
Code to reprudece NeurIPS paper: Accelerated Sparse Neural Training: A Provable and Efficient Method to Find N:M Transposable Masks
Accelerated Sparse Neural Training: A Provable and Efficient Method to FindN:M Transposable Masks Recently, researchers proposed pruning deep neural n
Approximate Nearest Neighbor Search for Sparse Data in Python!
Approximate Nearest Neighbor Search for Sparse Data in Python! This library is well suited to finding nearest neighbors in sparse, high dimensional spaces (like text documents).
Code for "Training Neural Networks with Fixed Sparse Masks" (NeurIPS 2021).
Code for "Training Neural Networks with Fixed Sparse Masks" (NeurIPS 2021).
Taichi is a parallel programming language for high-performance numerical computations.
Taichi is a parallel programming language for high-performance numerical computations.
Code for "Training Neural Networks with Fixed Sparse Masks" (NeurIPS 2021).
Fisher Induced Sparse uncHanging (FISH) Mask This repo contains the code for Fisher Induced Sparse uncHanging (FISH) Mask training, from "Training Neu
Implementation of Monocular Direct Sparse Localization in a Prior 3D Surfel Map (DSL)
DSL Project page: https://sites.google.com/view/dsl-ram-lab/ Monocular Direct Sparse Localization in a Prior 3D Surfel Map Authors: Haoyang Ye, Huaiya
Code for "Sparse Steerable Convolutions: An Efficient Learning of SE(3)-Equivariant Features for Estimation and Tracking of Object Poses in 3D Space"
Sparse Steerable Convolution (SS-Conv) Code for "Sparse Steerable Convolutions: An Efficient Learning of SE(3)-Equivariant Features for Estimation and
Learning to Map Large-scale Sparse Graphs on Memristive Crossbar
Release of AutoGMap:Learning to Map Large-scale Sparse Graphs on Memristive Crossbar For reproduction of our searched model, the Ubuntu OS is recommen
Official Python implementation of the 'Sparse deconvolution'-v0.3.0
Sparse deconvolution Python v0.3.0 Official Python implementation of the 'Sparse deconvolution', and the CPU (NumPy) and GPU (CuPy) calculation backen
Code for the paper "Attention Approximates Sparse Distributed Memory"
Attention Approximates Sparse Distributed Memory - Codebase This is all of the code used to run analyses in the paper "Attention Approximates Sparse D
This is the code related to "Sparse-to-dense Feature Matching: Intra and Inter domain Cross-modal Learning in Domain Adaptation for 3D Semantic Segmentation" (ICCV 2021).
Sparse-to-dense Feature Matching: Intra and Inter domain Cross-modal Learning in Domain Adaptation for 3D Semantic Segmentation This is the code relat
SparseLasso: Sparse Solutions for the Lasso
SparseLasso: Sparse Solutions for the Lasso Introduction SparseLasso provides a Scikit-Learn based estimation of the Lasso with cross-validation tunin
Code for "NeRS: Neural Reflectance Surfaces for Sparse-View 3D Reconstruction in the Wild," in NeurIPS 2021
Code for Neural Reflectance Surfaces (NeRS) [arXiv] [Project Page] [Colab Demo] [Bibtex] This repo contains the code for NeRS: Neural Reflectance Surf
Codes for 'Dual Parameterization of Sparse Variational Gaussian Processes'
Dual Parameterization of Sparse Variational Gaussian Processes Documentation | Notebooks | API reference Introduction This repository is the official
Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's algorithm.
Bayes-Newton Bayes-Newton is a library for approximate inference in Gaussian processes (GPs) in JAX (with objax), built and actively maintained by Wil
SEC'21: Sparse Bitmap Compression for Memory-Efficient Training onthe Edge
Training Deep Learning Models on The Edge Training on the Edge enables continuous learning from new data for deployed neural networks on memory-constr
Code for Paper "Evidential Softmax for Sparse MultimodalDistributions in Deep Generative Models"
Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models Abstract Many applications of generative models rely on the marginali
Meta-Learning Sparse Implicit Neural Representations (NeurIPS 2021)
Meta-SparseINR Official PyTorch implementation of "Meta-learning Sparse Implicit Neural Representations" (NeurIPS 2021) by Jaeho Lee*, Jihoon Tack*, N
PyTorch and GPyTorch implementation of the paper "Conditioning Sparse Variational Gaussian Processes for Online Decision-making."
Conditioning Sparse Variational Gaussian Processes for Online Decision-making This repository contains a PyTorch and GPyTorch implementation of the pa
This repository is the code of the paper "Sparse Spatial Transformers for Few-Shot Learning".
🌟 Sparse Spatial Transformers for Few-Shot Learning This code implements the Sparse Spatial Transformers for Few-Shot Learning(SSFormers). Our code i
This repository contains the code for the paper ``Identifiable VAEs via Sparse Decoding''.
Sparse VAE This repository contains the code for the paper ``Identifiable VAEs via Sparse Decoding''. Data Sources The datasets used in this paper wer
Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding
Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding
A toolset of Python programs for signal modeling and indentification via sparse semilinear autoregressors.
SPAAR Description A toolset of Python programs for signal modeling via sparse semilinear autoregressors. References Vides, F. (2021). Computing Semili
Python script for performing depth completion from sparse depth and rgb images using the msg_chn_wacv20. model in Tensorflow Lite.
TFLite-msg_chn_wacv20-depth-completion Python script for performing depth completion from sparse depth and rgb images using the msg_chn_wacv20. model
Transform-Invariant Non-Negative Matrix Factorization
Transform-Invariant Non-Negative Matrix Factorization A comprehensive Python package for Non-Negative Matrix Factorization (NMF) with a focus on learn
Development of IP code based on VIPs and AADM
Sparse Implicit Processes In this repository we include the two different versions of the SIP code developed for the article Sparse Implicit Processes
Efficient matrix representations for working with tabular data
Efficient matrix representations for working with tabular data
This is a library for training and applying sparse fine-tunings with torch and transformers.
This is a library for training and applying sparse fine-tunings with torch and transformers. Please refer to our paper Composable Sparse Fine-Tuning f
Motion and Shape Capture from Sparse Markers
MoSh++ This repository contains the official chumpy implementation of mocap body solver used for AMASS: AMASS: Archive of Motion Capture as Surface Sh
EM-POSE 3D Human Pose Estimation from Sparse Electromagnetic Trackers.
EM-POSE: 3D Human Pose Estimation from Sparse Electromagnetic Trackers This repository contains the code to our paper published at ICCV 2021. For ques
Advancing Self-supervised Monocular Depth Learning with Sparse LiDAR
Official implementation for paper "Advancing Self-supervised Monocular Depth Learning with Sparse LiDAR"
Python script for performing depth completion from sparse depth and rgb images using the msg_chn_wacv20. model in ONNX
ONNX msg_chn_wacv20 depth completion Python script for performing depth completion from sparse depth and rgb images using the msg_chn_wacv20 model in
Code for paper "Energy-Constrained Compression for Deep Neural Networks via Weighted Sparse Projection and Layer Input Masking"
model_based_energy_constrained_compression Code for paper "Energy-Constrained Compression for Deep Neural Networks via Weighted Sparse Projection and
Learning Sparse Neural Networks through L0 regularization
Example implementation of the L0 regularization method described at Learning Sparse Neural Networks through L0 regularization, Christos Louizos, Max W
Hierarchical unsupervised and semi-supervised topic models for sparse count data with CorEx
Anchored CorEx: Hierarchical Topic Modeling with Minimal Domain Knowledge Correlation Explanation (CorEx) is a topic model that yields rich topics tha
Efficient Sparse Attacks on Videos using Reinforcement Learning
EARL This repository provides a simple implementation of the work "Efficient Sparse Attacks on Videos using Reinforcement Learning" Example: Demo: Her
git-partial-submodule is a command-line script for setting up and working with submodules while enabling them to use git's partial clone and sparse checkout features.
Partial Submodules for Git git-partial-submodule is a command-line script for setting up and working with submodules while enabling them to use git's
[ICCV 2021 (oral)] Planar Surface Reconstruction from Sparse Views
Planar Surface Reconstruction From Sparse Views Linyi Jin, Shengyi Qian, Andrew Owens, David F. Fouhey University of Michigan ICCV 2021 (Oral) This re
🌈 PyTorch Implementation for EMNLP'21 Findings "Reasoning Visual Dialog with Sparse Graph Learning and Knowledge Transfer"
SGLKT-VisDial Pytorch Implementation for the paper: Reasoning Visual Dialog with Sparse Graph Learning and Knowledge Transfer Gi-Cheon Kang, Junseok P
Sparse R-CNN: End-to-End Object Detection with Learnable Proposals, CVPR2021
End-to-End Object Detection with Learnable Proposal, CVPR2021
Official code for paper "Demystifying Local Vision Transformer: Sparse Connectivity, Weight Sharing, and Dynamic Weight"
Demysitifing Local Vision Transformer, arxiv This is the official PyTorch implementation of our paper. We simply replace local self attention by (dyna
Compute descriptors for 3D point cloud registration using a multi scale sparse voxel architecture
MS-SVConv : 3D Point Cloud Registration with Multi-Scale Architecture and Self-supervised Fine-tuning Compute features for 3D point cloud registration
Differentiable Neural Computers, Sparse Access Memory and Sparse Differentiable Neural Computers, for Pytorch
Differentiable Neural Computers and family, for Pytorch Includes: Differentiable Neural Computers (DNC) Sparse Access Memory (SAM) Sparse Differentiab
A Planar RGB-D SLAM which utilizes Manhattan World structure to provide optimal camera pose trajectory while also providing a sparse reconstruction containing points, lines and planes, and a dense surfel-based reconstruction.
ManhattanSLAM Authors: Raza Yunus, Yanyan Li and Federico Tombari ManhattanSLAM is a real-time SLAM library for RGB-D cameras that computes the camera
PyTorch code for our paper "Image Super-Resolution with Non-Local Sparse Attention" (CVPR2021).
Image Super-Resolution with Non-Local Sparse Attention This repository is for NLSN introduced in the following paper "Image Super-Resolution with Non-
Fast sparse deep learning on CPUs
SPARSEDNN **If you want to use this repo, please send me an email: [email protected], or raise a Github issue. ** Fast sparse deep learning on CPUs
[Preprint] "Chasing Sparsity in Vision Transformers: An End-to-End Exploration" by Tianlong Chen, Yu Cheng, Zhe Gan, Lu Yuan, Lei Zhang, Zhangyang Wang
Chasing Sparsity in Vision Transformers: An End-to-End Exploration Codes for [Preprint] Chasing Sparsity in Vision Transformers: An End-to-End Explora
Stereo Radiance Fields (SRF): Learning View Synthesis for Sparse Views of Novel Scenes
Stereo Radiance Fields (SRF): Learning View Synthesis for Sparse Views of Novel Scenes
PyTorch implementation of: Michieli U. and Zanuttigh P., "Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations", CVPR 2021.
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations This is the official PyTorch implementation
Improving Deep Network Debuggability via Sparse Decision Layers
Improving Deep Network Debuggability via Sparse Decision Layers This repository contains the code for our paper: Leveraging Sparse Linear Layers for D
Block Sparse movement pruning
Movement Pruning: Adaptive Sparsity by Fine-Tuning Magnitude pruning is a widely used strategy for reducing model size in pure supervised learning; ho
Submanifold sparse convolutional networks
Submanifold Sparse Convolutional Networks This is the PyTorch library for training Submanifold Sparse Convolutional Networks. Spatial sparsity This li
CondenseNet V2: Sparse Feature Reactivation for Deep Networks
CondenseNetV2 This repository is the official Pytorch implementation for "CondenseNet V2: Sparse Feature Reactivation for Deep Networks" paper by Le Y