Greedy Growing Enables High-Resolution Pixel-Based Diffusion Models

no code implementations • 27 May 2024 • Cristina N. Vasconcelos, Abdullah Rashwan Austin Waters, Trevor Walker, Keyang Xu, Jimmy Yan, Rui Qian, Shixin Luo, Zarana Parekh, Andrew Bunner, Hongliang Fei, Roopal Garg, Mandy Guo, Ivana Kajic, Yeqing Li, Henna Nandwani, Jordi Pont-Tuset, Yasumasa Onoe, Sarah Rosston, Su Wang, Wenlei Zhou, Kevin Swersky, David J. Fleet, Jason M. Baldridge, Oliver Wang

Building on this core model, we propose a greedy algorithm that grows the architecture into high-resolution end-to-end models, while preserving the integrity of the pre-trained representation, stabilizing training, and reducing the need for large high-resolution datasets.

ImageInWords: Unlocking Hyper-Detailed Image Descriptions

1 code implementation • 5 May 2024 • Roopal Garg, Andrea Burns, Burcu Karagol Ayan, Yonatan Bitton, Ceslee Montgomery, Yasumasa Onoe, Andrew Bunner, Ranjay Krishna, Jason Baldridge, Radu Soricut

To address these issues, we introduce ImageInWords (IIW), a carefully designed human-in-the-loop annotation framework for curating hyper-detailed image descriptions and a new dataset resulting from this process.

Specificity Text-to-Image Generation

Agile Modeling: From Concept to Classifier in Minutes

no code implementations • ICCV 2023 • Otilia Stretcu, Edward Vendrow, Kenji Hata, Krishnamurthy Viswanathan, Vittorio Ferrari, Sasan Tavakkol, Wenlei Zhou, Aditya Avinash, Enming Luo, Neil Gordon Alldrin, Mohammadhossein Bateni, Gabriel Berger, Andrew Bunner, Chun-Ta Lu, Javier A Rey, Giulia Desalvo, Ranjay Krishna, Ariel Fuxman

In reaction, we introduce the problem of Agile Modeling: the process of turning any subjective visual concept into a computer vision model through a real-time user-in-the-loop interactions.

Image Classification