RESEARCH

SynSin: End-to-end View Synthesis from a Single Image

May 13, 2020

Abstract

View synthesis allows for the generation of new views ofa scene given one or more images. This is challenging; it requires comprehensively understanding the 3D scene from images. As a result, current methods typically use multiple images, train on ground-truth depth, or are limited to synthetic data. We propose a novel end-to-end model for this task using a single image at test time; it is trained on real images without any ground-truth 3D information. To this end, we introduce a novel differentiable point cloud renderer that is used to transform a latent 3D point cloud of features into the target view. The projected features are de-coded by our refinement network to inpaint missing regions and generate a realistic output image. The 3D component inside of our generative model allows for interpretable manipulation of the latent feature space at test time ,e.g. we can animate trajectories from a single image. Additionally, we can generate high resolution images and generalise to otherinput resolutions. We outperform baselines and prior work on the Matterport, Replica, and RealEstate10K datasets

Download the Paper

AUTHORS

Written by

Georgia Gkioxari

Justin Johnson

Rick Szeliski

Olivia Wiles

Publisher

CVPR

Related Publications

May 14, 2025

RESEARCH

CORE MACHINE LEARNING

UMA: A Family of Universal Models for Atoms

Brandon M. Wood, Misko Dzamba, Xiang Fu, Meng Gao, Muhammed Shuaibi, Luis Barroso-Luque, Kareem Abdelmaqsoud, Vahe Gharakhanyan, John R. Kitchin, Daniel S. Levine, Kyle Michel, Anuroop Sriram, Taco Cohen, Abhishek Das, Ammar Rizvi, Sushree Jagriti Sahoo, Zachary W. Ulissi, C. Lawrence Zitnick

May 14, 2025

May 13, 2025

HUMAN & MACHINE INTELLIGENCE

RESEARCH

Dynadiff: Single-stage Decoding of Images from Continuously Evolving fMRI

Marlène Careil, Yohann Benchetrit, Jean-Rémi King

May 13, 2025

April 25, 2025

RESEARCH

NLP

ReasonIR: Training Retrievers for Reasoning Tasks

Rulin Shao, Qiao Rui, Varsha Kishore, Niklas Muennighoff, Victoria Lin, Daniela Rus, Bryan Kian Hsiang Low, Sewon Min, Scott Yih, Pang Wei Koh, Luke Zettlemoyer

April 25, 2025

April 17, 2025

HUMAN & MACHINE INTELLIGENCE

CONVERSATIONAL AI

Collaborative Reasoner: Self-improving Social Agents with Synthetic Conversations

Ansong Ni, Ruta Desai, Yang Li, Xinjie Lei, Dong Wang, Ramya Raghavendra, Gargi Ghosh, Daniel Li (FAIR), Asli Celikyilmaz

April 17, 2025

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.