Seeing if I can put together an interactive version of 3b1b's Manim in Streamlit
sudo apt-get install -y libpango-1.0-0
Actually maybe this is what worked:
sudo apt install libpango1.0-dev pkg-config python3-dev
I got this from here.
Didn't work.
sudo apt install xorg-dev libglu1-mesa libgl1-mesa-dev xvfb libxinerama1 libxcursor1
USDAN The implementation of Unified unsupervised and semi-supervised domain adaptation network for cross-scenario face anti-spoofing, which is accepte
Answer_ALS_clinical_data Exploration of some patients clinical variables. All the clinical / metadata data is available here: https://data.answerals.o
El-Gamal-on-EC El-Gamal on Elliptic Curve (Python) References: https://docsdrive.com/pdfs/ansinet/itj/2005/299-306.pdf https://arxiv.org/ftp/arxiv/pap
MUGE Multimodal Retrieval Baseline This repo is implemented based on the open_cl
DTCN This is the implementation of our paper "Sequential Prediction of Social Me
Prototype-based Incremental Few-Shot Semantic Segmentation Fabio Cermelli, Massimiliano Mancini, Yongqin Xian, Zeynep Akata, Barbara Caputo -- BMVC 20
ICCV2021 Papers with Code
Finding Lane Lines on the Road Overview When we drive, we use our eyes to decide where to go. The lines on the road that show us where the lanes are a
Batch Active learning by Diverse Gradient Embeddings (BADGE) An implementation of the BADGE batch active learning algorithm. Details are provided in o
modern-slam-tutorial-python Learning and feeling SLAM together with hands-on-experiments ๐ ๐ ๐ Dependencies Most of the examples are based on GTSAM
Meterm a terminal with python ๐ How to use Clone Project: $ git clone https://github.com/motahharm/meterm.git Run: in Terminal: meterm.exe Or pip ins
This page contains a list of papers on multi-task learning for computer vision. Please create a pull request if you wish to add anything. If you are interested, consider reading our recent survey pap
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training Original implementation for paper GCC: Graph Contrastive Coding for Graph Neural N
Learning Modified Indicator Functions for Surface Reconstruction In this work, we propose a learning-based approach for implicit surface reconstructio
Awesome AutoDL A curated list of automated deep learning related resources. Inspired by awesome-deep-vision, awesome-adversarial-machine-learning, awe
How to eat TensorFlow2 in 30 days ? ๐ฅ ๐ฅ Click here for Chinese Version๏ผไธญๆ็๏ผ ใ10ๅคฉๅๆ้ฃๅชpysparkใ ๐ github้กน็ฎๅฐๅ: https://github.com/lyhue1991/eat_pyspark
Code for the paper "Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy" (arXiv:1611.04488; published at ICLR 2017), by Douga
Simple implementation of Equivariant GNN A short implementation of E(n) Equivariant Graph Neural Networks for HOMO energy prediction. Just 50 lines of
More Photos are All You Need: Semi-Supervised Learning for Fine-Grained Sketch Based Image Retrieval, CVPR 2021. Ayan Kumar Bhunia, Pinaki nath Chowdh
Music Source Separation with Channel-wise Subband Phase Aware ResUnet (CWS-PResUNet) Introduction This repo contains the pretrained Music Source Separ
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