This is the PyTorch repository for the GANnotation implementation. GANnotation is a landmark-guided face to face synthesis network that incorporates a triple consistency loss to bridge the gap between the input and target distributions Release v1 (Nov. 2018): Demo showing the performance of our ...
PyTorch2.0.0 PyTorch Lightning2.0.2 1 Nvidia GPU (RTX A6000 48GB) with CUDA version 11.7 To use video visualizer, please installffmpegby: sudo apt-get install ffmpeg For additional Python libraries, please install by: pip install -r requirements.txt ...
Official Implementation for "Consistency Flow Matching: Defining Straight Flows with Velocity Consistency" - consistency_flow_matching/run_lib_pytorch.py at main · YangLing0818/consistency_flow_matching
The implementation is based on the PyTorch 1.1 [39] framework. For optimization, we train for 50 epochs using SGD with a learning rate of 0.01 and a momentum of 0.9. During training, the learning rate is annealed following the poly learning rate policy, where...
GedankenNet, GedankenNet-Phaseand GedankenNet-Phaseλwere implemented using PyTorch94. We calculated the loss values based on the hologram amplitudes, that is: $$\hat{i}={\rm{|FSP}}\left(\hat{o}{\rm{;}}\,{z}_{1},{z}_{2},\cdots ,{z}_{M}\right){\rm{|}}$$ ...
需要注意的是,weak augmented得到的伪标签需要stop gradient(pytorch中通过detach) 本文提出的第一个论点是这种strong-weak augmentation的重要性(这在之前的文献中往往没有引起足够的重视,如CPS仅使用weak augmentation进行),在使用fixmatch+strong-weak augmentation+thr=0.95即可达到sota的结果(如下图) UniMatch 由此,可...
Publication:CVPR 2021论文地址: https://arxiv.org/pdf/2103.05465.pdf论文代码: GitHub - XuyangBai/PointDSC: [PyTorch] Official implementation of CVPR2021 paper "PointDSC: Robust Point Cloud Reg…
The weights of the DeepLab are initialized to the publicly available pre-trained COCO [4] model contained in the PyTorch [62] repository. The remaining layers are initialized as described in [52]. The nnU-Net is trained from scratch, i.e. without pretrained weights. 4.5.1. Augmentations Ap...
cdCCVC conda create -n CCVC python=3.6 conda activate CCVC pip install -r requirements.txt conda install pytorch==1.10.1 torchvision==0.11.2 torchaudio==0.10.1 cudatoolkit=11.3 -c pytorch -c conda-forge Please refer toUniMatchfor more implement details ...
PyTorch >= 1.0 torchvision >= 0.4 NumPy sklearn (optional) sklean is used for moon_data_exp.py (two moons dataset experiment) Usage One can usesh ./scripts/DATASET_NAME/ALGORITHM.sh /PATH/TO/OUTPUT_DIR NUM_LABELS, for example, to reproduce fixmatch in CIFAR-10 with 250 labels results,...