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Thrilled to share our new research on image-to-image translation, demonstrating strong performance across tasks like object relighting, shadow prediction, object removal, and depth and surface normal estimation. Check out our research paper, project page, demo, and Github repo👇

bro how the f*** is this working so well...

🌟 Exciting news in image-to-image translation! This new method achieves state-of-the-art results with just one inference step! Check out the amazing relighting demo showcased ! 🐶🎨✨

I love this!

This is soooo good.

I can't be more proud of the team!

Yesss Jasper introduces LBM: Latent Bridge Matching for Fast Image-to-Image Translation💡 and drops an amazing ✨image relighting✨ demo that runs with a single(!) inference step 🔥

New research drop! Our team at Jasper is redefining image-to-image translation with LBM: Latent Bridge Matching—a scalable approach to high-speed AI-powered image transformation. See it in action!

Introducing Mistral Small 3.1. Multimodal, Apache 2.0, outperforms Gemma 3 and GPT 4o-mini. mistral.ai/news/mistral-s…

🔥Wanna talk about combining diffusion models and sampling ?🔥 I'll be attending ICLR next week to present my work (main track + FPI workshop) with the one and only Louis Grenioux, we'll be pleased to discuss about this hot topic. See you there !

Very proud of the team!

Object Relighting with Latent Bridge Matching Link to Hugging Face space below + Link to Kijai's ComfyUI wrapper in first comment 👇

Proud to share the latest breakthrough from Jasper Research: Latent Bridge Matching (LBM) just got a major update! Our team has released three new open-source models on Hugging Face—supporting depth, normals, and relighting—along with training code and a Gradio demo for object

We’re thrilled to announce that the Jasper Research team’s latest paper on Latent Bridge Matching (LBM) was accepted to the prestigious IEEE/CVF International Conference on Computer Vision! Thank you #ICCV2025 for the recognition, and congratulations to the team:

Flash Diffusion is a breakthrough in accelerating conditional diffusion models for image generation. Think fewer steps, faster results, and state-of-the-art quality. Here's what you need to know: