RESEARCH

COMPUTER VISION

Wish You Were Here: Context-Aware Human Generation

June 13, 2020

Abstract

We present a novel method for inserting objects, specifically humans, into existing images, such that they blend in a photorealistic manner, while respecting the semantic context of the scene. Our method involves three subnetworks: the first generates the semantic map of the new person, given the pose of the other persons in the scene and an optional bounding box specification. The second network renders the pixels of the novel person and its blending mask, based on specifications in the form of multiple appearance components. A third network refines the generated face in order to match those of the target person. Our experiments present convincing high-resolution outputs in this novel and challenging application domain. In addition, the three networks are evaluated individually, demonstrating for example, state of the art results in pose transfer benchmarks.

Download the Paper

AUTHORS

Publisher

CVPR

Research Topics

Computer Vision

Related Publications

November 28, 2022

RESEARCH

CORE MACHINE LEARNING

Neural Attentive Circuits

Nicolas Ballas, Bernhard Schölkopf, Chris Pal, Francesco Locatello, Li Erran, Martin Weiss, Nasim Rahaman, Yoshua Bengio

November 28, 2022

November 27, 2022

RESEARCH

Near Instance-Optimal PAC Reinforcement Learning for Deterministic MDPs

Andrea Tirinzoni, Aymen Al Marjani, Emilie Kaufmann

November 27, 2022

November 16, 2022

RESEARCH

NLP

Memorization Without Overfitting: Analyzing the Training Dynamics of Large Language Models

Kushal Tirumala, Aram H. Markosyan, Armen Aghajanyan, Luke Zettlemoyer

November 16, 2022

November 10, 2022

RESEARCH

COMPUTER VISION

Learning State-Aware Visual Representations from Audible Interactions

Unnat Jain, Abhinav Gupta, Himangi Mittal, Pedro Morgado

November 10, 2022

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.