Ekaterina Sedykh@KateSedykh

During recent years, people started to produce more and more trash, polluting the planet. Even with continuing recycling, there is one important issue – trash on streets. It can be in already packaged bags or individual wrappers and bottles on the group, with some of it later being in the waters of Earth. The idea of the project is to create a trash detector using computer vision networks that can be used in 2 ways. Firstly, it can be integrated with already installed security cameras and have some software for trash collectors to use, so they would know where the trash is. Second more improved strategy is to create an automated robot which would collect the trash.

Synthesizing a novel view from different angles is an interest in many fields like VR, video enhancement, games, etc. However, this process has some limitations when given an image of an object from an unrecognizable angle. The proposed method combines image-to-image translation with stable diffusion by giving text as an additional parameter

It is our pleasure to welcome you to the third Cohere AI Hackathon! Our collaboration with Cohere gives lablab.ai community members access to one of the most powerful artificial intelligence language models available. Let's build a better future together! Join us and innovate!

It is our pleasure to welcome you to the Wolves Summit AI Hackathon. In partnership with Wolves Summit, we are giving the lablab.ai community an opportunity to develop an application to fight for a great cause - Saving Planet Earth. This is a preliminary event of the Wolves Summit conference that will take place in Vienna, Austria on 20-21 October 2022. Current world events show us that actions towards environmental safety are necessary. Do you have what it takes to protect the planet using Artificial Intelligence? Join us and innovate to build a better future for everyone!

A new text-to-image model called Stable Diffusion is set to change the game once again ⚡️. Stable Diffusion is a latent diffusion model that is capable of generating detailed images from text descriptions. It can also be used for tasks such as inpainting, outpainting, and image-to-image translations. Join us for a epic stable diffusion makers event 11-13 November 👊