We are a research group from Shanghai AI Lab focused on Vision-Centric AI research. The GV in our name, OpenGVLab, means general vision, a general understanding of vision, so little effort is needed to adapt to new vision-based tasks.
We develop model architecture and release pre-trained foundation models to the community to motivate further research in this area. We have made promising progress in general vision AI, with 109 SOTAš. In 2022, our open-sourced foundation model 65.5 mAP on the COCO object detection benchmark, 91.1% Top1 accuracy in Kinetics 400, achieved landmarks for AI visionš tasks for imageš¼ļø and videoš¹ understanding. In 2023, we created VideoChatš¦,llama-adapterš¦, 3D foundation model Ponder V2š§ and many more wonderful works! In CVPR 2023, our vision foundation model InternImage was listed as one of the most influential papers, and by benefiting from our partner OpenDriveLab, we won the Best paper togetherš .
In 2024, we released the best open-source VLM InternVL , video understanding foundation model InternVideo2, which won 7 Champions on EgoVis challenges š„. Up to now, our brilliant team have open-sourced more than 70 works, please find them hereš
Based on solid vision foundations, we have expanded to Multi-Modality models and. We aim to empower individuals and businesses by offering a higher starting point for developing vision-based AI products and lessening the burden of building an AI model from scratch.
Branchesļ¼ Alpha (explore lattest advances in vision+language research), uni-medical (focus on medical AI), Vchitect (Generative AIļ¼
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