ReSim This repository provides the PyTorch implementation of Region Similarity Representation Learning (ReSim) described in this paper: @Article{xiao2021region, author = {Tete Xiao and Colorado J Reed and Xiaolong Wang and Kurt Keutzer and Trevor Darrell}, title = {Region Similarity Representation Learning}, journal = {arXiv preprint arXiv:2103.12902}, year = {2021}, } tldr; ReSim maintains spatial relationships in the convolutional feature maps when performing instance contrastive pre-training, which is useful for region-related tasks such as object detection, segmentation, and dense pose estimation. […]

AntroPy AntroPy is a Python 3 package providing several time-efficient algorithms for computing the complexity of time-series. It can be used for example to extract features from EEG signals. Installation pip install antropy Functions Entropy import numpy as np import antropy as ant np.random.seed(1234567) x = np.random.normal(size=3000) # Permutation entropy print(ant.perm_entropy(x, normalize=True)) # Spectral entropy print(ant.spectral_entropy(x, sf=100, method=’welch’, normalize=True)) # Singular value decomposition entropy print(ant.svd_entropy(x, normalize=True)) # Approximate entropy print(ant.app_entropy(x)) # Sample entropy print(ant.sample_entropy(x)) # Hjorth mobility and complexity print(ant.hjorth_params(x)) […]

lightning-transformers Flexible interface for high-performance research using SOTA Transformers leveraging Pytorch Lightning, Transformers, and Hydra. Installation Option 1: from PyPI pip install lightning-transformers # instead of: `python train.py …`, run with: pl-transformers-train … Option 2: from source git clone https://github.com/PyTorchLightning/lightning-transformers.git cd lightning-transformers pip install . python train.py … # the `pl-transformers-train` endpoint is also available! Quick recipes Train bert-base-cased on the CARER emotion dataset using the Text Classification task. python train.py task=nlp/text_classification dataset=nlp/text_classification/emotion See the composed Hydra config used under-the-hood […]

Talking-Face_PC-AVS Pose-Controllable Talking Face Generation by Implicitly Modularized Audio-Visual Representation (CVPR 2021) We propose Pose-Controllable Audio-Visual System (PC-AVS), which achieves free pose control when driving arbitrary talking faces with audios. Instead of learning pose motions from audios, we leverage another pose source video to compensate only for head motions. The key is to devise an implicit low-dimension pose code that is free of mouth shape or identity information. In this way, audio-visual representations are modularized into spaces of three key […]