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3dmatch-toolbox

3DMatch - a 3D ConvNet-based local geometric descriptor for aligning 3D meshes and point clouds.

adaptsegnet

Learning to Adapt Structured Output Space for Semantic Segmentation, CVPR 2018 (spotlight)

caffe-lstm

LSTM implementation on Caffe

capsule-networks

A PyTorch implementation of the NIPS 2017 paper "Dynamic Routing Between Capsules".

continuouscrf-cnn

deformable-convnets-caffe

Deformable Convolutional Networks on caffe

demon

DeMoN: Depth and Motion Network

dense-spatial-transform-flow

Public Caffe implementation of Dense Spatial Transform Flow

diracnets

Training Very Deep Neural Networks Without Skip-Connections

drn

Dilated Residual Networks

drn-1

edges

Structured Edge Detection Toolbox

espnet

ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation

fc-densenet

Fully Convolutional DenseNets for semantic segmentation.

flownet2

FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks

flownet2-docker

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

flownet2-pytorch

Pytorch implementation of FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks

flownet3d

FlowNet3D: Learning Scene Flow in 3D Point Clouds

fusionnet-pytorch

FusionNet: A deep fully residual convolutional neural network for image segmentation in connectomics

geonet

Code for GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose (CVPR 2018)

google-research

Google Research

guidednet

Caffe implementation for "Guided Optical Flow Learning"

hed

code for Holistically-Nested Edge Detection

hidden-two-stream

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

instance-segmentation-pytorch

Semantic Instance Segmentation with a Discriminative Loss Function in PyTorch (https://arxiv.org/abs/1708.02551)

lightnet

LightNet: Light-weight Networks for Semantic Image Segmentation (Cityscapes and Mapillary Vistas Dataset)

liteflownet

LiteFlowNet: A Lightweight Convolutional Neural Network for Optical Flow Estimation, CVPR18 (Spotlight)

models

Models and examples built with TensorFlow

monodepth

Unsupervised single image depth prediction with CNNs

mrflow

Code for the paper "Optical Flow in Mostly Rigid Scenes" by Jonas Wulff, Laura Sevilla-Lara, Michael Black, CVPR 2017