August 27, 2021 NLP

Getting to Production with Few-shot Natural Language Generation Models

July 29, 2021 By: Peyman Heidari, Arash Einolghozati, Shashank Jain, Soumya Batra, Lee Callender, Ankit Arun, Shawn Mei, Sonal Gupta, Pinar Donmez, Vikas Bhardwaj, Anuj Kumar, Michael White Abstract In this paper, we study the utilization of pretrained language models to enable few-shot Natural Language Generation (NLG) in task-oriented dialog systems. We introduce a system consisting of iterative self-training and an extensible mini-template framework that textualizes the structured input data into semi-natural text to fully take advantage of pre-trained language […]

August 27, 2021 NLP

Text-Free Image-to-Speech Synthesis Using Learned Segmental Units

August 2, 2021 By: Wei-Ning Hsu, David Harwath, Tyler Miller, Christopher Song, James Glass Abstract In this paper we present the first model for directly synthesizing fluent, natural-sounding spoken audio captions for images that does not require natural language text as an intermediate representation or source of supervision. Instead, we connect the image captioning module and the speech synthesis module with a set of discrete, sub-word speech units that are discovered with a self-supervised visual grounding task. We conduct experiments […]

August 27, 2021 NLP

SUPERB: Speech Understanding and PERformance Benchmark

August 30, 2021 By: Shu-wen Yang, Po-Han Chi, Yung-Sung Chuang, Cheng-I Lai, Kushal Lakhotia, Yist Y. Lin, Andy T. Liu, Jiatong Shi, Xuankai Chang, Daniel Lin, Tzu-Hsien Huang, Wei-Cheng Tseng, Godic Lee, Darong Liu, Zili Huang, Annie Dong, Shang-Wen Li, Shinji Watanabe, Abdelrahman Mohamed, Hung-yi Lee Abstract Using self-supervised learning methods to pre-train a network on large volumes of unlabeled data followed by fine-tuning for multiple downstream tasks has proven vital for advancing research in natural language representation learning. However, […]

August 27, 2021 Deep Learning

Deep Unsupervised 3D SfM Face Reconstruction Based on Massive Landmark Bundle Adjustment

This repository shows two tasks: Face landmark detection and Face 3D reconstruction, which is described in this paper: Deep Unsupervised 3D SfM Face Reconstruction Based on Massive Landmark Bundle Adjustment. Installation Clone the repository. install dependencies. pip install -r requirement.txt Running a pre-trained model Download landmark pre-trained model at GoogleDrive, and put it into FaceLandmark/model/ Run the test file python Facial_landmark.py Running a pre-trained model Download face 3D reconstruction pre-trained model at GoogleDrive, and put it into FaceReconstruction/checkpoints/ Run the […]

August 27, 2021 Machine Learning

Sign-Agnostic Optimization of Convolutional Occupancy Networks

This repository contains the implementation of the paper: Sign-Agnostic CONet: Learning Implicit Surface Reconstructions by Sign-Agnostic Optimization of Convolutional Occupancy NetworksICCV 2021 (Oral) If you find our code or paper useful, please consider citing @inproceedings{tang2021sign, title={SA-ConvONet: Sign-Agnostic Optimization of Convolutional Occupancy Networks}, author={Tang, Jiapeng and Lei, Jiabao and Xu, Dan and Ma, Feiying and Jia, Kui and Zhang, Lei}, booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision}, year={2021} } Contact Jiapeng Tang for questions, comments and reporting bugs. Installation […]

August 27, 2021 Hardware

An open-source, low-cost, image-based weed detection device for fallow scenarios

OpenWeedLocator Welcome to the OpenWeedLocator (OWL) project, an opensource hardware and software green-on-brown weed detector that uses entirely off-the-shelf componentry, very simple green-detection algorithms and entirely 3D printable parts. OWL integrates weed detection on a Raspberry Pi with a relay control board in a custom designed case so you can attach any 12V solenoid, relay, lightbulb or device for low-cost, simple and opensource site-specific weed control. Projects to date have seen OWL mounted on robots and vehicles for spot spraying! […]

August 27, 2021 Transformer

A Transformer that Ponders, using the scheme from the PonderNet paper

Ponder(ing) Transformer Implementation of a Transformer that learns to adapt the number of computational steps it takes depending on the difficulty of the input sequence, using the scheme from the PonderNet paper. Will also try to abstract out a pondering module that can be used with any block that returns an output with the halting probability. This repository would not have been possible without repeated viewings of Yannic’s educational video Install $ pip install ponder-transformer Usage import torch from ponder_transformer […]

August 27, 2021 Detection

Industrial knn-based anomaly detection for images

Industrial KNN-based Anomaly Detection Industrial knn-based anomaly detection for images. Visit streamlit link to check out the demo. This repo aims to reproduce the results of the following KNN-based anomaly detection methods: SPADE (Cohen et al. 2021) – knn in z-space and distance to feature maps PaDiM* (Defard et al. 2020) – distance to multivariate Gaussian of feature maps PatchCore (Roth et al. 2021) – knn distance to avgpooled feature maps * actually does not have any knn mechanism, but […]

August 27, 2021 Unsupervised

Real-Time Unsupervised Anomaly Detection with Localization via Conditional Normalizing Flows

CFLOW-AD CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization via Conditional Normalizing FlowsWACV 2022 preprint:https://arxiv.org/abs/2107.12571 Abstract Unsupervised anomaly detection with localization has many practical applications when labeling is infeasible and, moreover, when anomaly examples are completely missing in the train data. While recently proposed models for such data setup achieve high accuracy metrics, their complexity is a limiting factor for real-time processing. In this paper, we propose a real-time model and analytically derive its relationship to prior methods. Our CFLOW-AD model […]

August 27, 2021 Network

An unofficial version of Alias-Free Generative Adversarial Networks

Alias-Free GAN An unofficial version of Alias-Free Generative Adversarial Networks (https://arxiv.org/abs/2106.12423). This repository was heavily based on Kim Seonghyeon’s (rosinality) implementation. The goal of this version is to be maintainable, easy to use, and expand the features of existing implementations. This is built using pytorch and pytorch lightning (a framework that abstracts away much of the hardware specific code). See open issues unsupported features, planned features, and current bugs. Licence This project is officially licensed as an MIT project. However, […]

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