July 3, 2021 API

A collection of metrics for evaluating timbre dissimilarity using the TorchMetrics API

A collection of metrics for evaluating timbre dissimilarity using the TorchMetrics API Installation pip install -e . Usage import timbremetrics datasets = timbremetrics.list_datasets() dataset = datasets[0] # get the first timbre dataset # MAE between target dataset and pred embedding distances metric = timbremetrics.TimbreMAE( margin=0.0, dataset=dataset, distance=timbremetrics.l1 ) # get numpy audio for the timbre dataset audio = timbremetrics.get_audio(dataset) # get arbitrary embeddings for the timbre dataset’s audio embeddings = net(audio) # compute the metric metric(embeddings) Metrics The following metrics […]

July 2, 2021 PyTorch

Look before you leap: learning landmark features for one-stage visual grounding

LBYL-Net This repo implements paper Look Before You Leap: Learning Landmark Features For One-Stage Visual Grounding CVPR 2021. Getting Started Prerequisites python 3.7 pytorch 10.0 cuda 10.0 gcc 4.92 or above Installation Then clone the repo and install dependencies. git clone https://github.com/svip-lab/LBYLNet.git cd LBYLNet pip install requirements.txt You also need to install our landmark feature convolution: cd ext git clone https://github.com/hbb1/landmarkconv.git cd landmarkconv/lib/layers python setup.py install –user We follow dataset structure DMS and FAOA. For convience, we have pack them […]

July 2, 2021 Machine Learning

A Novel Topology-Preserving Loss Function for Tubular Structure Segmentation

clDice CVPR 2021 Authors: Suprosanna Shit and Johannes C. Paetzold et al. @article{shit2020cldice, title={clDice – a Topology-Preserving Loss Function for Tubular Structure Segmentation}, author={Shit, Suprosanna and Paetzold, Johannes C and Sekuboyina, Anjany and Zhylka, Andrey and Ezhov, Ivan and Unger, Alexander and Pluim, Josien PW and Tetteh, Giles and Menze, Bjoern H}, journal={arXiv preprint arXiv:2003.07311}, year={2020} } Abstract Accurate segmentation of tubular, network-like structures, such as vessels, neurons, or roads, is relevant to many fields of research. For such structures, […]

July 2, 2021 Machine Learning

StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation

StyleSpace-pytorch Implementation of StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation (https://arxiv.org/pdf/2011.12799.pdf) in PyTorch This implementation is mostly relied on rosinality’s stylegan2-pytorch Requirements I have tested on: Usage For the index and channel, please check the paper (https://arxiv.org/pdf/2011.12799.pdf), e.g., (11_286), channel 286 of generator level 11. FFHQ Firstly, you should download pretrained model from here and place the stylegan2-ffhq-config-f.pkl into pretrained folder. Open the notebook StyleSpace_FFHQ.ipynb Car LSUN GitHub https://github.com/xrenaa/StyleSpace-pytorch

July 2, 2021 Machine Learning

Lidar sensors are frequently used in environment perception for autonomous vehicles

PointCloudDeNoising Point Cloud Denoising Abstract Lidar sensors are frequently used in environment perception for autonomous vehicles and mobile robotics to complement camera, radar, and ultrasonic sensors. Adverse weather conditions are significantly impacting the performance of lidar-based scene understanding by causing undesired measurement points that in turn effect missing detections and false positives.In heavy rain or dense fog, water drops could be misinterpreted as objects in front of the vehicle which brings a mobile robot to a full stop.In this paper, […]

July 2, 2021 Neural Network

An exact meshing solution from neural networks

AnalyticMesh Analytic Marching is an exact meshing solution from neural networks. Compared to standard methods, it completely avoids geometric and topological errors that result from insufficient sampling, by means of mathematically guaranteed analysis. This repository gives an implementation of Analytic Marching algorithm. This algorithm is initially proposed in our conference paper Analytic Marching: An Analytic Meshing Solution from Deep Implicit Surface Networks, then finally improved in our journal paper: Learning and Meshing from Deep Implicit Surface Networks Using an Efficient […]

July 2, 2021 Images

Content-Style Modulation for Image Retrieval with Text Feedback

CoSMo.pytorch Official Implementation of CoSMo: Content-Style Modulation for Image Retrieval with Text Feedback, Seungmin Lee*, Dongwan Kim*, Bohyung Han. *(denotes equal contribution) Setup Python: python3.7 Install required packages Install torch and torchvision via following command (CUDA10) pip install torch==1.2.0 torchvision==0.4.0 -f https://download.pytorch.org/whl/torch_stable.html Install other packages pip install -r requirements.txt Dataset Download the FashionIQ dataset by following the instructions on this link. We have set the default path for FashionIQ datasets in data/fashionIQ.py as _DEFAULT_FASHION_IQ_DATASET_ROOT = ‘/data/image_retrieval/fashionIQ’. You can change this […]

July 2, 2021 Machine Learning

Source-filter based Decomposed Modeling for Speech Synthesis

FastPitchFormant – PyTorch Implementation PyTorch Implementation of FastPitchFormant: Source-filter based Decomposed Modeling for Speech Synthesis. Dependencies You can install the Python dependencies with pip3 install -r requirements.txt Inference You have to download the pretrained models and put them in output/ckpt/LJSpeech/. For English single-speaker TTS, run python3 synthesize.py –text “YOUR_DESIRED_TEXT” –restore_step 1000000 –mode single -p config/LJSpeech/preprocess.yaml -m config/LJSpeech/model.yaml -t config/LJSpeech/train.yaml The generated utterances will be put in output/result/. Batch Inference Batch inference is also supported, try python3 synthesize.py –source preprocessed_data/LJSpeech/val.txt –restore_step […]

July 2, 2021 Text-to-Image

A Novel Dataset and A Text-Specific Refinement Approach

Rethinking Text Segmentation This is the repo to host the dataset TextSeg and code for TexRNet from the following paper: Xingqian Xu, Zhifei Zhang, Zhaowen Wang, Brian Price, Zhonghao Wang and Humphrey Shi, Rethinking Text Segmentation: A Novel Dataset and A Text-Specific Refinement Approach, ArXiv Link Note: [2021.04.21] So far, our dataset is partially released with images and semantic labels. Since many people may request the dataset for OCR or non-segmentation tasks, please stay tuned, and we will release the […]

July 2, 2021 Machine Learning

Robust Consistent Video Depth Estimation

robust_cvd This repository contains Python and C++ implementation of Robust Consistent Video Depth, as described in the paper Johannes Kopf, Xuejian Rong, and Jia-Bin Huang. Robust Consistent Video Despth Estimation. CVPR 2021 Project | Paper | Video | Colab We present an algorithm for estimating consistent dense depth maps and camera poses from a monocular video. We integrate a learning-based depth prior, in the form of a convolutional neural network trained for single-image depth estimation, with geometric optimization, to estimate […]

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