Your Daily AI Research tl;dr — 2022–06–30 🧠

Welcome to your official daily AI research tl;dr (often with code and news) for AI enthusiasts where I share the most exciting papers I find daily, along with a one-liner summary to help you quickly determine if the article (and code) is worth investigating. I will also take this opportunity to share daily exciting news in the field.

Let’s get started with this iteration!

1️⃣ NeuRIS: Neural Reconstruction of Indoor Scenes Using Normal Priors

Reconstructing high-quality 3D indoor scenes from 2D images integrating estimated normals of indoor scenes as a prior in a neural rendering framework for reconstructing large texture-less shapes and, importantly, to do this in an adaptive manner to also enable the reconstruction of irregular shapes with fine details.

Link to the paper: https://arxiv.org/abs/2206.13597

2️⃣ RetrieverTTS: Modeling Decomposed Factors for Text-Based Speech Insertion

They propose a new “decompose-and-edit” paradigm for the text-based speech insertion task that facilitates arbitrary length speech insertion and even full sentence generation by explicitly decomposing and separately manipulating global and local factors in speech to…