41 skills found · Page 1 of 2
advimman / Lama🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022
pkumivision / FFCThis is an official pytorch implementation of Fast Fourier Convolution.
USTCPCS / CVPR2018 AttentionContext Encoding for Semantic Segmentation MegaDepth: Learning Single-View Depth Prediction from Internet Photos LiteFlowNet: A Lightweight Convolutional Neural Network for Optical Flow Estimation PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume On the Robustness of Semantic Segmentation Models to Adversarial Attacks SPLATNet: Sparse Lattice Networks for Point Cloud Processing Left-Right Comparative Recurrent Model for Stereo Matching Enhancing the Spatial Resolution of Stereo Images using a Parallax Prior Unsupervised CCA Discovering Point Lights with Intensity Distance Fields CBMV: A Coalesced Bidirectional Matching Volume for Disparity Estimation Learning a Discriminative Feature Network for Semantic Segmentation Revisiting Dilated Convolution: A Simple Approach for Weakly- and Semi- Supervised Semantic Segmentation Unsupervised Deep Generative Adversarial Hashing Network Monocular Relative Depth Perception with Web Stereo Data Supervision Single Image Reflection Separation with Perceptual Losses Zoom and Learn: Generalizing Deep Stereo Matching to Novel Domains EPINET: A Fully-Convolutional Neural Network for Light Field Depth Estimation by Using Epipolar Geometry FoldingNet: Interpretable Unsupervised Learning on 3D Point Clouds Decorrelated Batch Normalization Unsupervised Learning of Depth and Egomotion from Monocular Video Using 3D Geometric Constraints PU-Net: Point Cloud Upsampling Network Real-Time Monocular Depth Estimation using Synthetic Data with Domain Adaptation via Image Style Transfer Tell Me Where To Look: Guided Attention Inference Network Residual Dense Network for Image Super-Resolution Reflection Removal for Large-Scale 3D Point Clouds PlaneNet: Piece-wise Planar Reconstruction from a Single RGB Image Fully Convolutional Adaptation Networks for Semantic Segmentation CRRN: Multi-Scale Guided Concurrent Reflection Removal Network DenseASPP: Densely Connected Networks for Semantic Segmentation SGAN: An Alternative Training of Generative Adversarial Networks Multi-Agent Diverse Generative Adversarial Networks Robust Depth Estimation from Auto Bracketed Images AdaDepth: Unsupervised Content Congruent Adaptation for Depth Estimation DeepMVS: Learning Multi-View Stereopsis GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose GeoNet: Geometric Neural Network for Joint Depth and Surface Normal Estimation Single-Image Depth Estimation Based on Fourier Domain Analysis Single View Stereo Matching Pyramid Stereo Matching Network A Unifying Contrast Maximization Framework for Event Cameras, with Applications to Motion, Depth, and Optical Flow Estimation Image Correction via Deep Reciprocating HDR Transformation Occlusion Aware Unsupervised Learning of Optical Flow PAD-Net: Multi-Tasks Guided Prediciton-and-Distillation Network for Simultaneous Depth Estimation and Scene Parsing Surface Networks Structured Attention Guided Convolutional Neural Fields for Monocular Depth Estimation TextureGAN: Controlling Deep Image Synthesis with Texture Patches Aperture Supervision for Monocular Depth Estimation Two-Stream Convolutional Networks for Dynamic Texture Synthesis Unsupervised Learning of Single View Depth Estimation and Visual Odometry with Deep Feature Reconstruction Left/Right Asymmetric Layer Skippable Networks Learning to See in the Dark
dealias / FftwppFast Fourier Transform C++ Header/MPI Transpose for FFTW3 with Implicitly Dealiased Convolutions
rhysnewell / FftconvolveRust implementations of Fast Fourier Transform convolution and correlation for n-dimensional arrays
pushkar-khetrapal / Fast CNNGenerating similiar results of convolution layers from Fast Fourier Transform
locuslab / Orthogonal ConvolutionsImplementations of orthogonal and semi-orthogonal convolutions in the Fourier domain with applications to adversarial robustness
Haozhoong / FCBFourier Convolution Block with global receptive field for MRI reconstruction pytorch
jloveric / High Order Layers TorchHigh order and sparse layers in pytorch. Lagrange Polynomial, Piecewise Lagrange Polynomial, Piecewise Discontinuous Lagrange Polynomial (Chebyshev nodes) and Fourier Series layers of arbitrary order. Piecewise implementations could be thought of as a 1d grid (for each neuron) where each grid element is Lagrange polynomial. Both full connected and convolutional layers included.
1911cty / Unbiased Fast Fourier ConvolutionICCV2023 Rethinking Fast Fourier Convolution in Image Inpainting
luciaquirke / Sleep ApneaConvolutional neural network which uses 30 second single-channel EEG signals to detect apnea events. Kernels are visualised using Fourier transforms.
grahman / RTConvolveJuce-based audio plugin for single-threaded real time convolution of long (or short) impulse responses provided by the user. Uses Hurchalla's time-distributed fast Fourier Transform for efficient convolution.
soleilssss / FFCNetFFCNet: Fourier Transform-Based Frequency Learning and Complex Convolutional Network for Colon Disease Classification (MICCAI 2022)
FurongHuang / ConvDicLearnTensorFactorTensor methods have emerged as a powerful paradigm for consistent learning of many latent variable models such as topic models, independent component analysis and dictionary learning. Model parameters are estimated via CP decomposition of the observed higher order input moments. However, in many domains, additional invariances such as shift invariances exist, enforced via models such as convolutional dictionary learning. In this paper, we develop novel tensor decomposition algorithms for parameter estimation of convolutional models. Our algorithm is based on the popular alternating least squares method, but with efficient projections onto the space of stacked circulant matrices. Our method is embarrassingly parallel and consists of simple operations such as fast Fourier transforms and matrix multiplications. Our algorithm converges to the dictionary much faster and more accurately compared to the alternating minimization over filters and activation maps.
rileyedmunds / Complexcnnresearch on convolutional neural networks in fourier space
Farid-Tasharofi / FIND NetFIND-Net (Fourier-Integrated Network with Dictionary Kernels) is a deep learning model for Metal Artifact Reduction (MAR) in CT imaging. It integrates Fast Fourier Convolution (FFC) and trainable Gaussian filtering to suppress artifacts while preserving anatomical structures.
brettbuddin / Fourier👩🔬 A Fast Fourier Transform and Partitioned Convolution Library
z0gSh1u / QftpyQuaternion Fourier Transform and Convolution for Python
deependra227 / Real Time Audio Filtering Using PythonPlatform for Audio Filtering (Digital Filters) in Real-Time using Convolution Theorem and Fast Fourier Transform.
Bychin / S2kitFast Fourier Transforms and Convolutions of functions defined on sphere
