778 Open source projects that are alternatives of or similar to Pwc Net

LiteFlowNet: A Lightweight Convolutional Neural Network for Optical Flow Estimation, CVPR 2018 (Spotlight paper, 6.6%)

A Lightweight Optical Flow CNN - Revisiting Data Fidelity and Regularization, TPAMI 2020

No dependency caffe replacement

Caffe implementation for "Guided Optical Flow Learning"

Unsupervised Deep Hashing with Similarity-Adaptive and Discrete Optimization (TPAMI2018)

DilatedNet in Keras for image segmentation

Active Convolution

Frame-Recurrent Video Super-Resolution (official repository)

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Dockerfile and runscripts for FlowNet 2.0 (estimation of optical flow)

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CNN model inference benchmarks for some popular deep learning frameworks

把极速检测器的门槛给我打下来make lightweight caffe-ssd great again

[High Performance / MAX 30 FPS] RaspberryPi3(RaspberryPi/Raspbian Stretch) or Ubuntu + Multi Neural Compute Stick(NCS/NCS2) + RealSense D435(or USB Camera or PiCamera) + MobileNet-SSD(MobileNetSSD) + Background Multi-transparent(Simple multi-class segmentation) + FaceDetection + MultiGraph + MultiProcessing + MultiClustering

Caffe implementation of "Fast and Accurate Single Image Super-Resolution via Information Distillation Network" (CVPR 2018)

Optical Flow Prediction with TensorFlow. Implements "PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume," by Deqing Sun et al. (CVPR 2018)

MobileNet-SSD(MobileNetSSD) + Neural Compute Stick(NCS) Faster than YoloV2 + Explosion speed by RaspberryPi · Multiple moving object detection with high accuracy.

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

Training & Quantization of embedded friendly Deep Learning / Machine Learning / Computer Vision models

Dockerfile and runscripts for DispNet and FlowNet1 (estimation of disparity and optical flow)

AI on Hadoop

Caffe: a Fast framework for deep learning. Custom version with built-in sparse inputs, segmentation, object detection, class weights, and custom layers

Fabric for Deep Learning (FfDL, pronounced fiddle) is a Deep Learning Platform offering TensorFlow, Caffe, PyTorch etc. as a Service on Kubernetes

FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks

Real-time Detectron using webcam.

Adaptive and Focusing Neural Layers for Multi-Speaker Separation Problem

An online GUI tool used to visualize prototxt and generate prototxt for caffe(current version).

Head Pose Estimator on Caffe

Data-centric declarative deep learning framework

A deep convolutional neural network system for live emotion detection

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🏭 Collaboratively build, visualize, and design neural nets in browser

keras를 이용한 딥러닝 기초 학습

Deep learning face detection and recognition, implemented by pytorch. (pytorch实现的人脸检测和人脸识别)

Bidirectional Attention Flow for Machine Comprehension implemented in Keras 2

Multi-class confusion matrix library in Python

Programming assignments from all courses in the Coursera Natural Language Processing Specialization offered by deeplearning.ai.

DeeplabV2 segmentation in Keras.

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Paperspace API for python

Self Maintained Caffe. In this version Faster-RCNN, RFCN needs layer are fully supported!

AI智能审查，支持色情识别、暴恐识别、语言识别、敏感文字检测和视频检测等功能，以及各种OCR识别能力，如身份证、驾照、行驶证、营业执照、银行卡、手写体、车牌和名片识别等功能，可以访问网站体验功能。

Python tutorials as Jupyter Notebooks for NLP, ML, AI

Bottom-up attention model for image captioning and VQA, based on Faster R-CNN and Visual Genome

Example code for the ADNS-3080 optical flow sensor

Training Toolbox for Caffe

The implementation of Relativistic average GAN with Keras

Algorithms Tutorial

ROS Error-State Kalman Filter based on PX4/ecl. Performs GPS/Magnetometer/Vision Pose/Optical Flow/RangeFinder fusion with IMU

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FeatherCNN is a high performance inference engine for convolutional neural networks.

Unsupervised Learning for Image Registration

Sentiment analysis on tweets using Naive Bayes, SVM, CNN, LSTM, etc.

Computer code collated for use with Artificial Intelligence Engines book by JV Stone

This repository stores the files used for my summer internship's work on "teacher-student learning", an experimental method for training deep neural networks using a trained teacher model.

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Deep Recurrent Q-Learning vs Deep Q Learning on a simple Partially Observable Markov Decision Process with Minecraft