RESEARCH

COMPUTER VISION

Exploring Crowd Co-creation Scenarios for Sketches

July 11, 2020

Abstract

As a first step towards studying the ability of human crowds and machines to effectively co-create, we explore several human-only collaborative co-creation scenarios. The goal in each scenario is to create a digital sketch using a simple web interface. We find that settings in which multiple humans iteratively add strokes and vote on the best additions result in sketches with the highest creativity (combination of value and novelty). Lack of collaboration leads to a higher variance in quality and lower novelty or surprise. Collaboration without voting leads to high novelty but low quality.

Download the Paper

AUTHORS

Written by

Devi Parikh

Larry Zitnick

Publisher

International Conference on Computational Creativity (ICCC)

Research Topics

Computer Vision

Related Publications

April 16, 2026

RESEARCH

AIRA₂: Overcoming Bottlenecks in AI Research Agents

Karen Hambardzumyan, Nicolas Baldwin, Edan Toledo, Rishi Hazra, Michael Kuchnik, Bassel Al Omari, Thomas Simon Foster, Anton Protopopov, Jean-Christophe Gagnon-Audet, Ishita Mediratta, Kelvin Niu, Michael Shvartsman, Alisia Lupidi, Alexis Audran-Reiss, Parth Pathak, Tatiana Shavrina, Despoina Magka, Hela Momand, Derek Dunfield, Nicola Cancedda, Pontus Stenetorp, Carole-Jean Wu, Jakob Foerster, Yoram Bachrach, Martin Josifoski

April 16, 2026

April 14, 2026

COMPUTER VISION

ML APPLICATIONS

TransText: Transparency Aware Image-to-Video Typography Animation

Fei Zhang, Zijian Zhou, Bohao Tang, Sen He, Hang Li (BizAI), Zhe Wang, Soubhik Sanyal, Pengfei Liu, Viktar Atliha, Tao Xiang, Frost Xu, Semih Gunel

April 14, 2026

April 09, 2026

HUMAN & MACHINE INTELLIGENCE

COMPUTER VISION

Think in Strokes, Not Pixels: Process-Driven Image Generation via Interleaved Reasoning

Lei Zhang, Junjiao Tian, Zhipeng Fan, Kunpeng Li, Jialiang Wang, Weifeng Chen, Markos Georgopoulos, Felix Xu, Yuxiao Bao, Julian McAuley, Manling Li, Zecheng He

April 09, 2026

March 17, 2026

RESEARCH

NLP

Omnilingual MT: Machine Translation for 1,600 Languages

Omnilingual MT Team, Belen Alastruey, Niyati Bafna, Andrea Caciolai, Kevin Heffernan, Artyom Kozhevnikov, Christophe Ropers, Eduardo Sánchez, Charles-Eric Saint-James, Ioannis Tsiamas, Chierh CHENG, Joe Chuang, Paul-Ambroise Duquenne, Mark Duppenthaler, Nate Ekberg, Cynthia Gao, Pere Lluís Huguet Cabot, João Maria Janeiro, Jean Maillard, Gabriel Mejia Gonzalez, Holger Schwenk, Edan Toledo, Arina Turkatenko, Albert Ventayol-Boada, Rashel Moritz, Alexandre Mourachko, Surya Parimi, Mary Williamson, Shireen Yates, David Dale, Marta R. Costa-jussa

March 17, 2026

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.