Oliiveralien

Oliiveralien

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UPC-CVLab

Oliiveralien's repositories

Inpainting-review

Paper, code, pretained model for mainstream inpainting methods since 2000

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CPNet

Context-aware Pretraining for Efficient Blind Image Decomposition (CVPR'23)

MDMS

Multi-Domain Multi-Scale Diffusion Model for Low-Light Image Enhancement (AAAI'24)

AdaDSR

Deep Adaptive Inference Networks for Single Image Super-Resolution

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Awesome-pytorch-list

A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

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deeplearning-models

A collection of various deep learning architectures, models, and tips

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DyNet

Code, results and evaluations of the paper "Multi-Dimensional Dynamic Pruning: Exploring Spatial and Channel Fuzzy Sparsity"

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MDCP

Code, results and evaluations of the paper ''Multi-Domain Clustering Pruning: Exploring Space and Frequency Similarity Based on GAN' in Neurocomputing.

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Oliver-Inpainting

Code, Demo and Results of the homework paper for DL class in UPC

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Oliver-TimeSeriesForecast

Code, Demo and Results of the homework program for DL class in UPC.

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GLCIC-PyTorch

A High-Quality PyTorch Implementation of "Globally and Locally Consistent Image Completion".

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Inpaint-Anything

Inpaint anything using Segment Anything and inpainting models.

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Inpainting-test

Test for inpainting metrics on irregular holes

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iptv

Collection of 5000+ publicly available IPTV channels from all over the world

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pyconv

Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual Recognition (https://arxiv.org/pdf/2006.11538.pdf)

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pytorch-doc-zh

Pytorch 中文文档

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RN

Region Normalization for Image Inpainting, accepted by AAAI-2020

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UPC-nCoV-submit

自动填写**石油大学(华东)疫情防控通

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vcnet-blind-image-inpainting

Reproduction of "VCNet: A Robust Approach to Blind Image Inpainting"

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vit-pytorch

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

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WXF

利用 Github Action 实现UPC疫情防控通自动上报,不需要服务器或云服务。

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