Investigating Prompt Engineering in Diffusion Models

21 November 2022

Papers citing "Investigating Prompt Engineering in Diffusion Models"

8 / 8 papers shown

Title
FRAP: Faithful and Realistic Text-to-Image Generation with Adaptive Prompt Weighting Liyao Jiang Negar Hassanpour Mohammad Salameh Mohan Sai Singamsetti Fengyu Sun Wei Lu Di Niu DiffM 139 2 0 21 Aug 2024
LAION-5B: An open large-scale dataset for training next generation image-text models Christoph Schuhmann Romain Beaumont Richard Vencu Cade Gordon Ross Wightman ... Srivatsa Kundurthy Katherine Crowson Ludwig Schmidt R. Kaczmarczyk J. Jitsev VLM MLLM CLIP 200 3,502 0 16 Oct 2022
Hierarchical Text-Conditional Image Generation with CLIP Latents Aditya A. Ramesh Prafulla Dhariwal Alex Nichol Casey Chu Mark Chen VLM DiffM 425 6,921 0 13 Apr 2022
GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models Alex Nichol Prafulla Dhariwal Aditya A. Ramesh Pranav Shyam Pamela Mishkin Bob McGrew Ilya Sutskever Mark Chen 368 3,630 0 20 Dec 2021
A Loss Function for Generative Neural Networks Based on Watson's Perceptual Model Steffen Czolbe Oswin Krause Ingemar Cox Christian Igel GAN 48 49 0 26 Jun 2020
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks Nils Reimers Iryna Gurevych 1.3K 12,332 0 27 Aug 2019
The Unreasonable Effectiveness of Deep Features as a Perceptual Metric Richard Y. Zhang Phillip Isola Alexei A. Efros Eli Shechtman Oliver Wang EGVM 384 11,938 0 11 Jan 2018
Perceptual Losses for Real-Time Style Transfer and Super-Resolution Justin Johnson Alexandre Alahi Li Fei-Fei SupR 262 10,273 0 27 Mar 2016