Text-to-image diffusion models have recently received increasing interest for their astonishing ability to produce high-fidelity images from solely text inputs. Subsequent research efforts aim to exploit and apply their capabilities to real image editing. However, existing image-to-image methods are often inefficient, imprecise, and of limited versatility. They either require time-consuming fine-tuning, deviate unnecessarily strongly from the input image, and/or lack support for multiple, simultaneous edits. To address these issues, we introduce LEDITS++, an efficient yet versatile and precise textual image manipulation technique. LEDITS++'s novel inversion approach requires no tuning nor optimization and produces high-fidelity results with a few diffusion steps. Second, our methodology supports multiple simultaneous edits and is architecture-agnostic. Third, we use a novel implicit masking technique that limits changes to relevant image regions. We propose the novel TEdBench++ benchmark as part of our exhaustive evaluation. Our results demonstrate the capabilities of LEDITS++ and its improvements over previous methods. The project page is available at https://leditsplusplus-project.static.hf.space .

This week's paper may just be your next favorite model to date. If you think the recent image generation models like DALLE or Stable Diffusion are cool, you just won't believe how incredible this one is. Imagic takes such a diffusion-based model able to take text and generate images out of it and adapts the model to edit the images. You can generate an image and then teach the model to edit it any way you want. Read the full article: https://www.louisbouchard.ai/imagic/

By the first few months of 1982, it had become more common to see electronics stores, toy stores, and discount variety stops selling 2600 games. This was before Electronics Boutique, Software Etc., and later, GameStop . Mostly you bought games at stores that sold other electronic products, like Sears or Consumer Distributors. Toys'R' Us was a big seller of 2600 games. To buy one, you had to get a piece of paper from the Atari aisle, bring it to the cashier, pay for it, and then wait at a pickup window behind the cash register lanes. Everyone had a favorite store in their childhood; here's a story about one of mine. A popular "destination" in south Brooklyn is Kings Plaza, a giant (for Brooklyn) two-story indoor mall with about 100 stores. My mother and grandmother were avid shoppers there. To get to the mall from our house, it was about a 10-minute car service ride. So once a week or thereabouts, we'd all go. The best part for me was when we went inside via its Avenue U entrance instead of on the Flatbush Avenue side.