Pinned Repositories
3D-Machine-Learning
A resource repository for 3D machine learning
3D-ResNets-PyTorch
3D ResNets for Action Recognition
AdelaiDet
AdelaiDet is an open source toolbox for multiple instance-level detection and recognition tasks.
AI-Challenger-Keypoints-pytorch
AI Challenger Keypoints Detection(https://challenger.ai/competition/keypoint/leaderboard) (SYSU_Pose Rank #6)
FaceDatasets
Some scripts to process face datasets.
frcnn
Faster R-CNN C++ version based on Caffe; support approximate joint train.
Image_Captioning_AI_Challenger
Code for AI Challenger contest. (Generating chinese image captions)
Parking-slot-dataset
Parking slot dataset for different scenes
Parking-slot-detection
Parking slot detection code and model
TJP-datasets
TJP object detection datasets
wuzzh's Repositories
wuzzh/caffe-tools
Some tools and examples for pyCaffe including LMDB I/O, custom Python layers and monitoring training error and loss.
wuzzh/CaffePythonLayerLoss
wuzzh/CascadeCNN
Repository for "A Convolutional Neural Network Cascade for Face Detection", implemented with Caffe, C++ interface
wuzzh/DeepFace
Face analysis mainly based on Caffe. At this time, face analysis tasks like detection, alignment and recognition have been done.
wuzzh/denet
A simple extendable library for training and evaluating Deep Convolutional Neural Networks focussing on real-time image classification and detection.
wuzzh/Focal-Loss
Reproduction of Focal-loss on caffe
wuzzh/MOTDemo
Multi Object Tracking Demo(traffic statistics & passenger flow statistics)
wuzzh/nms-speedup
A highly parallelized implementation of non-maximum suppression for object detection used for self-driving cars.
wuzzh/RMPE
RMPE: Regional Multi-person Pose Estimation, forked from Caffe. Research purpose only.
wuzzh/rrc_detection
Accurate Single Stage Detector Using Recurrent Rolling Convolution
wuzzh/spencer_people_tracking
Multi-modal ROS-based people detection and tracking framework for mobile robots developed within the context of the EU FP7 project SPENCER.
wuzzh/ThiNet
caffe model of ICCV'17 paper - ThiNet: A Filter Level Pruning Method for Deep Neural Network Compression https://arxiv.org/abs/1707.06342