Deep Learning

Representing Scenes as Compositional Generative Neural Feature Fields

GIRAFFE This repository contains the code for the CVPR 2021 paper “GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields” GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields If you find our code or paper useful, please cite as @inproceedings{GIRAFFE, title = {GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields}, author = {Niemeyer, Michael and Geiger, Andreas}, booktitle = {Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR)}, year = {2021} } TL; DR – Quick Start […]

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PyTorch

Invert and perturb GAN images for test-time ensembling

GAN Ensembling Ensembling with Deep Generative Views.Lucy Chai, Jun-Yan Zhu, Eli Shechtman, Phillip Isola, Richard ZhangCVPR 2021 Prerequisites Linux Python 3 NVIDIA GPU + CUDA CuDNN Table of Contents: Colab – run a limited demo version without local installation Setup – download required resources Quickstart – short demonstration code snippet Notebooks – jupyter notebooks for visualization Pipeline – details on full pipeline We project an input image into the latent space of a pre-trained GAN and perturb it slightly to […]

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GUI

A collection of modern themes for Tkinter TTK

ttkbootstrap A collection of modern flat themes inspired by Bootstrap. Also includes TTK Creator which allows you to easily create and use your own themes. How to install pip install ttkbootstrap If you are on Linux, you may need to install a font with emojii support. sudo apt-get install fonts-symbola Documentation Read for more information about how to use along with full-size screenshots, and other useful information. https://ttkbootstrap.readthedocs.io/en/latest/ Sample of themes Play with a live demo after installing the package […]

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Dataset

Task-based datasets, preprocessing, and evaluation for sequence models

SeqIO SeqIO is a library for processing sequential data to be fed into downstream sequence models. It uses tf.data.Dataset to create scalable data pipelines but requires minimal use of TensorFlow. In particular, with one line of code, the returned dataset can be transformed to a numpy iterator and hence it is fully compatible with other frameworks such as JAX or PyTorch. Currently, SeqIO assumes that the dataset is a sequence, i.e., each feature is one-dimensional array. Modalities such as text […]

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Telegram

A Telegram Parmanent Files Store Bot

PyroFilesStoreBot This is Telegram Parmanent Files Store Bot by @AbirHasan2005. Language: Python3Library: Pyrogram Features: In PM Just Forward or Send any file it will save on Database & give you the Access Link. In Channel Add Bot as Admin with Edit Rights. When you will send any file or media in Channel it will Edit the Broadcast Message with Saved Link Button. You can also Broadcast anythings via this Bot. You can also Do Force Sub to a Channel to […]

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Segmentation

Discriminative Region Suppression for Weakly-Supervised Semantic Segmentation

DRS Official pytorch implementation of our paper: Discriminative Region Suppression for Weakly-Supervised Semantic Segmentation [Paper], Beomyoung Kim, Sangeun Han, and Junmo Kim, AAAI 2021 We propose the discriminative region suppression (DRS) module that is a simple yet effective method to expand object activation regions. DRS suppresses the attention on discriminative regions and spreads it to adjacent non-discriminative regions, generating dense localization maps. [2021.06.10] we support DeepLab-V3 segmentation network! Setup Dataset Preparing # dataset structure VOC2012/ — Annotations/ — ImageSets/ — […]

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Segmentation

Efficient Regional Memory Network for Video Object Segmentation

RMNet This repository contains the source code for the paper Efficient Regional Memory Network for Video Object Segmentation. Cite this work @inproceedings{xie2021efficient, title={Efficient Regional Memory Network for Video Object Segmentation}, author={Xie, Haozhe and Yao, Hongxun and Zhou, Shangchen and Zhang, Shengping and Sun, Wenxiu}, booktitle={CVPR}, year={2021} } Datasets We use the ECSSD, COCO, PASCAL VOC, MSRA10K, DAVIS, and YouTube-VOS datasets in our experiments, which are available below: Pretrained Models The pretrained models for DAVIS and YouTube-VOS are available as follows: […]

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Neural Network

Statistically Signifigant Stopping of Neural Network Training

ASWS This codebase is being actively maintained, please create and issue if you have issues using it Code to use Augmented Shapiro Wilks Stopping, as well as code for the paper “Statistically Signifigant Stopping of Neural Network Training” Basics All data files are included under losses and each folder. The main Augmented Shapiro-Wilk Stopping criterion is implemented in analysis.py, along with several helper functions and wrappers. The other comparison heuristics are also included in analysis.py, along with their wrappers. grapher.py […]

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Video

Semi-supervised video object segmentation evaluation in python

MiVOS (CVPR 2021) – Mask Propagation [CVPR 2021] MiVOS – Mask Propagation module. Reproduced STM (and better) with training code . Semi-supervised video object segmentation evaluation. Ho Kei Cheng, Yu-Wing Tai, Chi-Keung Tang New! See our new STCN for a better and faster algorithm. This repo implements an improved version of the Space-Time Memory Network (STM) and is part of the accompanying code of Modular Interactive Video Object Segmentation: Interaction-to-Mask, Propagation and Difference-Aware Fusion (MiVOS). It can be used as: […]

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Machine Learning

Causal Inference and Machine Learning in Practice with EconML and CausalML

kdd2021-tutorial Causal Inference and Machine Learning in Practice with EconML and CausalML: Industrial Use Cases at Microsoft, TripAdvisor, Uber Schedule Time 4:00 AM – 7:00 AM August 15, 2021 SGT 4:00 PM – 7:00 PM August 14, 2021 EDT 1:00 PM – 4:00 PM August 14, 2021 PDT Live Zoom Link To be shared within the KDD 21 Virtual Platform during the conference. Abstract In recent years, both academic research and industry applications see an increased effort in using machine […]

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