EVA: Visual Representation Fantasies from BAAI
EVA is an innovative project developed by the Beijing Academy of Artificial Intelligence (BAAI) that focuses on advancing visual representation learning. The project encompasses various models and research efforts aimed at enhancing our understanding and capability in interpreting and utilizing visual data. Below is a closer look at the key components of the EVA project.
EVA-01
EVA-01 is a pioneering effort in the field of masked visual representation learning, presented at the CVPR 2023 conference, and recognized as a highlight of the event. This model explores the boundaries of what can be achieved with large-scale visual representation learning, pushing the limits of current technologies and methodologies in deciphering and synthesizing visual information.
EVA-02
EVA-02 is featured in the Image and Vision Computing domain and is considered a significant contribution to the visual representation of concepts drawn from Neon Genesis. This effort builds on the insights gained from EVA-01, furthering the project’s aim to create more sophisticated tools for image recognition and processing.
EVA-CLIP
Described in an Arxiv 2023 paper, EVA-CLIP introduces refined training techniques to optimize the performance of CLIP (Contrastive Language–Image Pretraining) at scale. This model focuses on improving the efficiency and accuracy of training methods for dealing with large datasets, making notable advancements over previous iterations.
EVA-CLIP-18B
An upcoming component detailed in Arxiv 2024, EVA-CLIP-18B scales the CLIP model to 18 billion parameters. This expansion aims to significantly enhance the model's ability to comprehend and process vast amounts of visual and textual data, promising a leap forward in the field of foundation models.
EVA @ Hugging Face 🤗 & timm
The EVA project has also extended its reach to the Hugging Face platform, providing implementations such as eva02_large_patch14_448.mim_m38m_ft_in1k. Similarly, EVA-CLIP is available on both Hugging Face and open_clip, allowing broader access to the model through tools like eva02_enormous_patch14_plus_clip_224.laion2b_s9b_b144k.
Contact and Opportunities
The BAAI Vision Team is actively looking for talents across various levels, including full-time researchers, engineers, and interns. Anyone interested in foundational models, self-supervised learning, and multimodal learning is encouraged to reach out via Xinlong Wang's email.
Licensing and Community
The EVA project is shared under a specific license, ensuring that its use, distribution, and modification adhere to set guidelines. The community around the project is growing, with opportunities to engage, star, and fork the project repository available on platforms like GitHub.
The EVA project represents a significant step forward in visual representation learning, promising to deliver new insights and tools for the interpretation of visual data in artificial intelligence.