324 Open source projects that are alternatives of or similar to PCLNet

Caffe implementation for "Guided Optical Flow Learning"

Unsupervised Learning for Image Registration

UnFlow: Unsupervised Learning of Optical Flow with a Bidirectional Census Loss

SelFlow: Self-Supervised Learning of Optical Flow

Unsupervised Learning of Multi-Frame Optical Flow with Occlusions

DDFlow: Learning Optical Flow with Unlabeled Data Distillation

Unsupervised Learning of Multi-Frame Optical Flow with Occlusions

The official PyTorch implementation of the paper "Learning by Analogy: Reliable Supervision from Transformations for Unsupervised Optical Flow Estimation".

TensorFlow implementation for "Guided Optical Flow Learning"

Competitive Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion Segmentation

Caffe implementation for "Hidden Two-Stream Convolutional Networks for Action Recognition"

[MICCAI'18] Joint Learning of Motion Estimation and Segmentation for Cardiac MR Image Sequences

Pure Pytorch implementation of Correlation Layer that commonly used in learning based optical flow estimator

Official implementation of the CVPR 2022 paper "DETReg: Unsupervised Pretraining with Region Priors for Object Detection".

SALT (iccv2017) based Video Denoising Codes, Matlab implementation

[ICCV 2021 Oral] High-Resolution Optical Flow from 1D Attention and Correlation

ROS package for Correlation Flow (ICRA 2018)

[ICCV2021] Learning to Track Objects from Unlabeled Videos

PyTorch code for NeurIPSW 2020 paper (4th Workshop on Meta-Learning) "Few-Shot Unsupervised Continual Learning through Meta-Examples"

Official repository of Learning Multi-Human Optical Flow (IJCV 2019)

Awesome Graph Self-Supervised Learning

Vector Quantized Autoregressive Predictive Coding (VQ-APC)

Experiments on unsupervised point cloud reconstruction.

Convolutional AutoEncoder application on MRI images

SESF-Fuse: An Unsupervised Deep Model for Multi-Focus Image Fusion

An implementation of "Community Preserving Network Embedding" (AAAI 2017)

Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations. [NeurIPS 2021]

Unsupervised learning of action classes with continuous temporal embedding (CVPR'19)

Semantic Structure-based Unsupervised Deep Hashing IJCAI2018

Extract video features from raw videos using multiple GPUs. We support RAFT and PWC flow frames as well as S3D, I3D, R(2+1)D, VGGish, CLIP, ResNet features.

📖Learning reinforcement learning by implementing the algorithms from reinforcement learning an introduction

Every Pixel Counts ++: Joint Learning of Geometry and Motion with 3D Holistic Understanding

Image2Image Translation Research

pyMCR: Multivariate Curve Resolution for Python

This is a master project of some experiments with Neural Networks. Every project here is runnable, visualized and explained clearly.

Dual CNN Models for Unsupervised Monocular Depth Estimation

Deep Metric Transfer for Label Propagation with Limited Annotated Data

Image Denoising Codes using STROLLR learning, the Matlab implementation of the paper in ICASSP2017

TOD: GPU-accelerated Outlier Detection via Tensor Operations

Code release for "Learning Shape Abstractions by Assembling Volumetric Primitives " (CVPR 2017)

Optical Flow Dataset and Benchmark for Visual Crowd Analysis

Code repository for paper `Skeleton Merger: an Unsupervised Aligned Keypoint Detector`.

Pytorch implementation of four neural network based domain adaptation techniques: DeepCORAL, DDC, CDAN and CDAN+E. Evaluated on benchmark dataset Office31.

Attacking Optical Flow (ICCV 2019)

Official adversarial mixup resynthesis repository

Unsupervised Learning to Market Behavior Forecasting Example

A NetworkX implementation of Label Propagation from a "Near Linear Time Algorithm to Detect Community Structures in Large-Scale Networks" (Physical Review E 2008).

Neural Relation Understanding: neural cardinality estimators for tabular data

machine learning algorithms in Swift

PyTrx is a Python object-oriented programme created for the purpose of calculating real-world measurements from oblique images and time-lapse image series. Its primary purpose is to obtain velocities, surface areas, and distances from oblique, optical imagery of glacial environments.

official implemntation for "Contrastive Learning with Stronger Augmentations"

OpenMMLab optical flow toolbox and benchmark

An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.

Bridging Stereo Matching and Optical Flow via Spatiotemporal Correspondence, CVPR 2019

Linguistica 5: Unsupervised Learning of Linguistic Structure

Video Representation Learning by Recognizing Temporal Transformations. In ECCV, 2020.

Main component extraction for outlier detection

Awesome-Cross-Domain-Person-Re-identification

Image based obstacle avoidance using optical flow

Unsupervised machine learning Principal Component Analysis (PCA) on the Dow Jones Industrial Average index and it's respective 30 stocks to construct an optimized diversified intelligent portfolio.