Machine-in-the-Loop Rewriting for Creative Image Captioning

Last update: Jul 24, 2022

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Overview

Machine-in-the-Loop Rewriting for Creative Image Captioning

Data

Annotated sources of data used in the paper:

Data Source	URL
Mohammed et al.	Link
Gordon et al.	Link
Bostan et al.	Link
Niculae et al.	Link
Steen et al.	Link

TODO: Individual data cleaning scripts

Model Training

Follow the README in the model_training directory to train a Fairseq BART model. Reach out for our trained model.

Interface

Code to run the UI we used for interactive experiments. This UI hosts a server and needs you to have a backend GPU to run model inference during interaction. The code saves each interaction with a unique ID which we use to match to our crowdworkers for experimental analysis.

TODO: Data Processing Scripts to filter results

Owner

Vishakh P

GitHub Repository

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Machine-in-the-Loop Rewriting for Creative Image Captioning

Related tags

Overview

Machine-in-the-Loop Rewriting for Creative Image Captioning

Data

TODO: Individual data cleaning scripts

Model Training

Interface

TODO: Data Processing Scripts to filter results

Owner

Vishakh P

The deployment framework aims to provide a simple, lightweight, fast integrated, pipelined deployment framework that ensures reliability, high concurrency and scalability of services.

An official source code for "Augmentation-Free Self-Supervised Learning on Graphs"

Implementation of the method described in the Speech Resynthesis from Discrete Disentangled Self-Supervised Representations.

Cereal box identification in store shelves using computer vision and a single train image per model.

Diverse Object-Scene Compositions For Zero-Shot Action Recognition

HiPAL: A Deep Framework for Physician Burnout Prediction Using Activity Logs in Electronic Health Records

Hierarchical probabilistic 3D U-Net, with attention mechanisms (—𝘈𝘵𝘵𝘦𝘯𝘵𝘪𝘰𝘯 𝘜-𝘕𝘦𝘵, 𝘚𝘌𝘙𝘦𝘴𝘕𝘦𝘵) and a nested decoder structure with deep supervision (—𝘜𝘕𝘦𝘵++).

A developer interface for creating Chat AIs for the Chai app.

How will electric vehicles affect traffic congestion and energy consumption: an integrated modelling approach

Implementation of SETR model, Original paper: Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers.

[ICCV 2021] Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neural Networks in Frequency Domain

Source code for our paper "Empathetic Response Generation with State Management"

Over-the-Air Ensemble Inference with Model Privacy

Official implementation of "SinIR: Efficient General Image Manipulation with Single Image Reconstruction" (ICML 2021)

Experiments for Fake News explainability project

Pytorch implementation of Cut-Thumbnail in the paper Cut-Thumbnail:A Novel Data Augmentation for Convolutional Neural Network.

LVI-SAM: Tightly-coupled Lidar-Visual-Inertial Odometry via Smoothing and Mapping

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Data and code for ICCV 2021 paper Distant Supervision for Scene Graph Generation.

Predicting Price of house by considering ,house age, Distance from public transport