14 citations · 14 across the 3 of their papers we have counts for
4 papers
UniFusion: Vision-Language Model as Unified Encoder in Image Generation
Kevin Li, Manuel Brack, Sudeep Katakol +2
Although recent advances in visual generation have been remarkable, most existing architectures still depend on distinct encoders for images and text. This separation constrains di…
How to Train your Text-to-Image Model: Evaluating Design Choices for Synthetic Training Captions
Manuel Brack, Sudeep Katakol, Felix Friedrich +4
Training data is at the core of any successful text-to-image models. The quality and descriptiveness of image text are crucial to a model's performance. Given the noisiness and inc…
DANICE: Domain adaptation without forgetting in neural image compression
Sudeep Katakol, Luis Herranz, Fei Yang +1
Neural image compression (NIC) is a new coding paradigm where coding capabilities are captured by deep models learned from data. This data-driven nature enables new potential funct…
Distributed Learning and Inference with Compressed Images
Sudeep Katakol, Basem Elbarashy, Luis Herranz +2
Modern computer vision requires processing large amounts of data, both while training the model and/or during inference, once the model is deployed. Scenarios where images are capt…