caffeCaffe: a Fast framework for deep learning. Custom version with built-in sparse inputs, segmentation, object detection, class weights, and custom layers
Stars: ✭ 36 (+28.57%)
vqa-softAccompanying code for "A Simple Loss Function for Improving the Convergence and Accuracy of Visual Question Answering Models" CVPR 2017 VQA workshop paper.
Stars: ✭ 14 (-50%)
bert-AADAdversarial Adaptation with Distillation for BERT Unsupervised Domain Adaptation
Stars: ✭ 27 (-3.57%)
XLearning-GPUqihoo360 xlearning with GPU support; AI on Hadoop
Stars: ✭ 22 (-21.43%)
superpixelRefinementSuperpixel-based Refinement for Object Proposal Generation (ICPR 2020)
Stars: ✭ 24 (-14.29%)
pytorch-ardaA PyTorch implementation for Adversarial Representation Learning for Domain Adaptation
Stars: ✭ 49 (+75%)
caffe exampleinstall script and example for clCaffe which will run caffe by OpenCL (this is for https://github.com/01org/caffe/tree/inference-optimize)
Stars: ✭ 12 (-57.14%)
DLInfBenchCNN model inference benchmarks for some popular deep learning frameworks
Stars: ✭ 51 (+82.14%)
domain adaptDomain adaptation networks for digit recognitioning
Stars: ✭ 14 (-50%)
EmotionChallengeSource code for 1st winner of face micro-emotion competition, FG 2017.
Stars: ✭ 37 (+32.14%)
domain-adaptation-caplsUnsupervised Domain Adaptation via Structured Prediction Based Selective Pseudo-Labeling
Stars: ✭ 43 (+53.57%)
caffe-demoCollection of deep learning demos based on neworks from the Caffe Zoo
Stars: ✭ 15 (-46.43%)
ganslateSimple and extensible GAN image-to-image translation framework. Supports natural and medical images.
Stars: ✭ 17 (-39.29%)
KD3AHere is the official implementation of the model KD3A in paper "KD3A: Unsupervised Multi-Source Decentralized Domain Adaptation via Knowledge Distillation".
Stars: ✭ 63 (+125%)
deep-parkingCode to reproduce 'Deep Learning for Decentralized Parking Lot Occupancy Detection' paper.
Stars: ✭ 81 (+189.29%)
fusion ganCodes for the paper 'Learning to Fuse Music Genres with Generative Adversarial Dual Learning' ICDM 17
Stars: ✭ 18 (-35.71%)
darknet2caffeConversion of yolo from DarkNet to Caffe
Stars: ✭ 25 (-10.71%)
ddrlDeep Developmental Reinforcement Learning
Stars: ✭ 27 (-3.57%)
Classification NetsImplement popular models by different DL framework. Such as tensorflow and caffe
Stars: ✭ 17 (-39.29%)
facial-landmarksFacial landmarks detection with OpenCV, Dlib, DNN
Stars: ✭ 25 (-10.71%)
cmdCentral Moment Discrepancy for Domain-Invariant Representation Learning (ICLR 2017, keras)
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SSD TrackerCounting people, dog and bicycle using SSD detection and tracking.
Stars: ✭ 17 (-39.29%)
nsfw apiPython REST API to detect images with adult content
Stars: ✭ 71 (+153.57%)
chainer-ADDAAdversarial Discriminative Domain Adaptation in Chainer
Stars: ✭ 24 (-14.29%)
TensorRT-LPR车牌识别,基于HyperLPR实现,修改模型调用方法,使用caffe+tensorRT实现GPU加速,修改了车牌检测模型
Stars: ✭ 14 (-50%)
FDCNNThe implementation of FDCNN in paper - A Feature Difference Convolutional Neural Network-Based Change Detection Method
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DRCNPytorch implementation of Deep Reconstruction Classification Networks
Stars: ✭ 31 (+10.71%)
game-feature-learningCode for paper "Cross-Domain Self-supervised Multi-task Feature Learning using Synthetic Imagery", Ren et al., CVPR'18
Stars: ✭ 68 (+142.86%)
MobilenetSSD caffeHow to train and verify mobilenet by using voc pascal data in caffe ssd?
Stars: ✭ 25 (-10.71%)
BIFI[ICML 2021] Break-It-Fix-It: Unsupervised Learning for Program Repair
Stars: ✭ 74 (+164.29%)
caffeThis fork of BVLC/Caffe is dedicated to supporting Cambricon deep learning processor and improving performance of this deep learning framework when running on Machine Learning Unit(MLU).
Stars: ✭ 40 (+42.86%)
adversarial-attacksCode for our CVPR 2018 paper, "On the Robustness of Semantic Segmentation Models to Adversarial Attacks"
Stars: ✭ 90 (+221.43%)
weak-supervision-for-NERFramework to learn Named Entity Recognition models without labelled data using weak supervision.
Stars: ✭ 114 (+307.14%)
ppqPPL Quantization Tool (PPQ) is a powerful offline neural network quantization tool.
Stars: ✭ 281 (+903.57%)
LoveDA[NeurIPS2021 Poster] LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation
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TrainCaffeCustomDatasetTransfer learning in Caffe: example on how to train CaffeNet on custom dataset
Stars: ✭ 20 (-28.57%)
all-classifiers-2019A collection of computer vision projects for Acute Lymphoblastic Leukemia classification/early detection.
Stars: ✭ 24 (-14.29%)
CADAAttending to Discriminative Certainty for Domain Adaptation
Stars: ✭ 17 (-39.29%)
R2CNNcaffe re-implementation of R2CNN: Rotational Region CNN for Orientation Robust Scene Text Detection
Stars: ✭ 80 (+185.71%)
CAM-PythonClass Activation Mapping with Caffe using the Python wrapper pycaffe instead of matlab.
Stars: ✭ 66 (+135.71%)