Subject
4 entries
Clip
Bookmarks
EVA: Exploring the Limits of Masked Visual Representation Learning at Scale
EVA is a 1-billion-parameter vision foundation model from BAAI that achieves state-of-the-art on image classification, detection, and segmentation by pretraining a ViT to reconstruct masked CLIP features. Initializing CLIP's vision tower from EVA dramatically stabilizes training — an important practical finding for building large multimodal systems.
CLIP Interrogator
CLIP Interrogator by pharmapsychotic is a Google Colab tool that reverse-engineers what prompt would produce a given image — using CLIP to describe an image in terms that Stable Diffusion understands. The go-to tool in 2022 for figuring out how to replicate an image style.
Alien Dreams: CLIP-Guided Image Generation
UC Berkeley ML blog's 2021 post on using CLIP for guided image generation — an early exploration of the CLIP+VQGAN/diffusion pipeline that preceded Stable Diffusion. Historically significant as a snapshot of generative AI before it became mainstream.
Deep Daze: Text to Image with CLIP and Siren
Deep Daze is Phil Wang's early text-to-image tool combining OpenAI's CLIP with Siren (implicit neural representations) — one of the first accessible open-source implementations of text-guided image generation, predating DALL-E and Stable Diffusion by over a year.