Pinned Repositories
adaptive-weighted-gans
aimet
AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.
Attention
Awesome-ICCV2021-Low-Level-Vision
A Collection of Papers and Codes for ICCV2021 Low Level Vision and Image Generation
Base-quantization
base quantization methods including: QAT, PTQ, per_channel, per_tensor, dorefa, lsq, adaround, omse, Histogram, bias_correction.etc
CalibTIP
Improving Post Training Neural Quantization: Layer-wise Calibration and Integer Programming
CharbonnierLoss
cnn-quantization
Quantization of Convolutional Neural networks.
contextualLoss
The Contextual Loss
focal-frequency-loss
[ICCV 2021] Focal Frequency Loss for Image Reconstruction and Synthesis
xd1073321804's Repositories
xd1073321804/CharbonnierLoss
xd1073321804/focal-frequency-loss
[ICCV 2021] Focal Frequency Loss for Image Reconstruction and Synthesis
xd1073321804/adaptive-weighted-gans
xd1073321804/aimet
AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.
xd1073321804/Attention
xd1073321804/Awesome-ICCV2021-Low-Level-Vision
A Collection of Papers and Codes for ICCV2021 Low Level Vision and Image Generation
xd1073321804/Base-quantization
base quantization methods including: QAT, PTQ, per_channel, per_tensor, dorefa, lsq, adaround, omse, Histogram, bias_correction.etc
xd1073321804/CalibTIP
Improving Post Training Neural Quantization: Layer-wise Calibration and Integer Programming
xd1073321804/cnn-quantization
Quantization of Convolutional Neural networks.
xd1073321804/DASR
Training and Testing codes for our paper "Real-world Image Super-resolution via Domain-distance Aware Training"
xd1073321804/dd3d
dd3d_supp
xd1073321804/dd3d_official
Official PyTorch implementation of DD3D: Is Pseudo-Lidar needed for Monocular 3D Object detection? (ICCV 2021), Dennis Park*, Rares Ambrus*, Vitor Guizilini, Jie Li, and Adrien Gaidon.
xd1073321804/DeepLearningSystem
Deep Learning System core principles introduction.
xd1073321804/ESRGANplus
ICASSP 2020 - ESRGAN+ : Further Improving Enhanced Super-Resolution Generative Adversarial Network - ICPR 2020 - Tarsier: Evolving Noise Injection in Super-Resolution GANs
xd1073321804/Fer2013-Facial-Emotion-Recognition-Pytorch
This method achieves SOTA single model accuracy of 73.70 % on FER2013 without using extra training data.
xd1073321804/first-order-model
This repository contains the source code for the paper First Order Motion Model for Image Animation
xd1073321804/IPTV-URL
xd1073321804/ISP
Image Signal Processor
xd1073321804/MANet
Official PyTorch code for Mutual Affine Network for Spatially Variant Kernel Estimation in Blind Image Super-Resolution (MANet, ICCV2021)
xd1073321804/mmediting
MMEditing is a low-level vision toolbox based on PyTorch, supporting super-resolution, inpainting, matting, video interpolation, etc.
xd1073321804/netron
Visualizer for neural network, deep learning, and machine learning models
xd1073321804/PaddleDetection_YOLOSeries
🚀🚀🚀 YOLO Series of PaddleDetection implementation, PPYOLOE, YOLOX, YOLOv7, YOLOv5, MT-YOLOv6 and so on. 🚀🚀🚀
xd1073321804/pix2pixHD
Synthesizing and manipulating 2048x1024 images with conditional GANs
xd1073321804/PScode
xd1073321804/pytorch-CycleGAN-and-pix2pix
Image-to-Image Translation in PyTorch
xd1073321804/pytorch-distributed
多GPU分布式训练
xd1073321804/testUpload
xd1073321804/visual_pts
visual point clouds (with bbox) by Plotly
xd1073321804/Vulkan
Examples and demos for the new Vulkan API
xd1073321804/xdhzhang1995
Config files for my GitHub profile.