RESEARCH
SPEECH & AUDIO
Unsupervised Object Segmentation by Redrawing
December 07, 2019
Abstract
Object segmentation is a crucial problem that is usually solved by using supervised learning approaches over very large datasets composed of both images and corresponding object masks. Since the masks have to be provided at pixel level, building such a dataset for any new domain can be very time-consuming. We present ReDO, a new model able to extract objects from images without any annotation in an unsupervised way. It relies on the idea that it should be possible to change the textures or colors of the objects without changing the overall distribution of the dataset. Following this assumption, our approach is based on an adversarial architecture where the generator is guided by an input sample: given an image, it extracts the object mask, then redraws a new object at the same location. The generator is controlled by a discriminator that ensures that the distribution of generated images is aligned to the original one. We experiment with this method on different datasets and demonstrate the good quality of extracted masks.
AUTHORS
Written by
Ludovic Denoyer
Mickael Chen
Thierry Artieres
Publisher
NeurIPS
Related Publications
April 14, 2024
SPEECH & AUDIO
NLP
CoLLD: Contrastive Layer-to-Layer Distillation for Compressing Multilingual Pre-Trained Speech Encoders
Heng-Jui Chang, Ning Dong (AI), Ruslan Mavlyutov, Sravya Popuri, Andy Chung
April 14, 2024
December 11, 2023
SPEECH & AUDIO
Audiobox: Unified Audio Generation with Natural Language Prompts
Wei-Ning Hsu, Akinniyi Akinyemi, Alice Rakotoarison, Andros Tjandra, Apoorv Vyas, Baishan Guo, Bapi Akula, Bowen Shi, Brian Ellis, Ivan Cruz, Jeff Wang, Jiemin Zhang, Mary Williamson, Matt Le, Rashel Moritz, Robbie Adkins, William Ngan, Xinyue Zhang, Yael Yungster, Yi-Chiao Wu
December 11, 2023
November 30, 2023
SPEECH & AUDIO
NLP
Efficient Monotonic Multihead Attention
Xutai Ma, Anna Sun, Siqi Ouyang, Hirofumi Inaguma, Paden Tomasello
November 30, 2023
November 30, 2023
SPEECH & AUDIO
NLP
Seamless: Multilingual Expressive and Streaming Speech Translation
Seamless Communication, Loïc Barrault, Yu-An Chung, Mariano Coria Meglioli, David Dale, Ning Dong, Mark Duppenthaler, Paul-Ambroise Duquenne, Brian Ellis, Hady Elsahar, Justin Haaheim, John Hoffman, Min-Jae Hwang, Hirofumi Inaguma, Christopher Klaiber, Ilia Kulikov, Pengwei Li, Daniel Licht, Jean Maillard, Ruslan Mavlyutov, Alice Rakotoarison, Kaushik Ram Sadagopan, Abinesh Ramakrishnan, Tuan Tran, Guillaume Wenzek, Yilin Yang, Ethan Ye, Ivan Evtimov, Pierre Fernandez, Cynthia Gao, Prangthip Hansanti, Elahe Kalbassi, Amanda Kallet, Artyom Kozhevnikov, Gabriel Mejia Gonzalez, Robin San Roman, Christophe Touret, Corinne Wong, Carleigh Wood, Bokai Yu, Pierre Andrews, Can Balioglu, Peng-Jen Chen, Marta R. Costa-jussà, Maha Elbayad, Hongyu Gong, Francisco Guzmán, Kevin Heffernan, Somya Jain, Justine Kao, Ann Lee, Xutai Ma, Alexandre Mourachko, Benjamin Peloquin, Juan Pino, Sravya Popuri, Christophe Ropers, Safiyyah Saleem, Holger Schwenk, Anna Sun, Paden Tomasello, Changhan Wang, Jeff Wang, Skyler Wang, Mary Williamson
November 30, 2023
Help Us Pioneer The Future of AI
We share our open source frameworks, tools, libraries, and models for everything from research exploration to large-scale production deployment.
Product experiences
Foundational models
Product experiences
Latest news
Foundational models
Meta © 2024