lorna-liu Goto Github PK

attention-gated-networks

Use of Attention Gates in a Convolutional Neural Network / Medical Image Classification and Segmentation

caffe

Caffe: a fast open framework for deep learning.

caffe-1

This fork of BVLC/Caffe is dedicated to improving performance of this deep learning framework when running on CPU, in particular Intel® Xeon processors (HSW+) and Intel® Xeon Phi processors

caltech-pedestrian-dataset-converter

Download Caltech Pedestrian Dataset and convert them for Python users without using MATLAB

citypersons2voc

A tool that converts CityPersons dataset into PASCAL VOC format.

conv_arithmetic

A technical report on convolution arithmetic in the context of deep learning

couplenet

Code for training 'CoupleNet: Coupling Global Structure with Local Parts for Object Detection' in ICCV 2017

deformable-convnets

Deformable Convolutional Networks

deformable-convnets-caffe

Deformable Convolutional Networks on caffe

eval_kitti

Tools to evaluate object detection results using the KITTI dataset.

lorna-liu.github.io

lyxtmpl

LyX templates and examples for several conferences and thesis

mscnn

Caffe implementation of our multi-scale object detection framework

mx-rcnn

Parallel Faster R-CNN implementation with MXNet.

opencvexamples

learning about OpenCV

pseudo-3d-pytorch

pytorch version of pseudo-3d-residual-networks(P-3D), pretrained model is supported

pspnet

Pyramid Scene Parsing Network

py-faster-rcnn-caltech-pedestrian

Faster R-CNN (Python implementation) -- see https://github.com/ShaoqingRen/faster_rcnn for the official MATLAB version

py-r-fcn-multigpu

Code for training py-faster-rcnn and py-R-FCN on multiple GPUs in caffe

pytorch-vslud

This is the implementation of the paper Video Summarization by Learning from Unpaired Data(CVPR2019)

r-fcn.pytorch

A Pytorch Implementation of R-FCN/CoupleNet

rcf

Richer Convolutional Features for Edge Detection

rpn_bf

RPN+BF

toolbox

Piotr's Image & Video Matlab Toolbox

ultrasound_vsumm_rl

Ultrasound Video Summarization using Deep Reinforcement Learning

website