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论文名:T-Rex2:Towards Generic Object Detection via Text-Visual Prompt Synergy 论文链接: https://arxiv.org/pdf/2403.14610.pdf项目链接: https://github.com/IDEA-Research/TRex导读目标检测是计算机视…
最新最有趣的科技前沿内容 GitHub-IDEA-Research/T-Rex:T-Rex2:通过文本视觉提示协同实现通用目标检测 内容导读: T-Rex2是一种前沿的目标检测模型,以其独特的识别图像中物体的方法脱颖而出。与传统模型只能识别固定类别不同,T-Rex2利用文本和视觉提示的组合,使其能够在没有事先特定训练的情况下识别各种物体。这...
T-Rex2 API:https://github.com/IDEA-Research/T-Rex 论文链接:https://arxiv.org/abs/2403.14610 关于我们 深圳市人工智能产业协会成立于2019年,坚持党建引领,对标德国技术监督协会(TÜV ),秉持为人工智能产业服务的宗旨,以成为国际...
git clone https://github.com/IDEA-Research/T-Rex.gitcdT-Rex pip install dds-cloudapi-sdk==0.1.1 pip install -v -e. Interactive Visual Prompt API In interactive visual prompt workflow, users can provide visual prompts in boxes or points format on a given image to specify the object to ...
- T-Rex2的模型API现已在GitHub上提供。 按照物体类别的出现频率,目标检测从闭集走向text prompt,目前正向着visual prompt发展。 通过text prompt和visual prompt的协同互补,可以起到在不同频谱上全覆盖的协同效果。 在有region-text配对训练数据的情况下,还可以做contrastive alignment,一方面text prompt相对抽象,可以起...
现在,T-Rex2让通用物体检测又迈出了新的一步。 试玩链接: https://deepdataspace.com/playground/ivp T-Rex2API:https://github.com/IDEA-Research/T-Rex 论文链接: https://arxiv.org/abs/2403.14610 —完—
API code is available at https://github.com/IDEA-Research/T-Rex .Jiang, QingInternational Digital Economy Academy (IDEA)Li, FengThe Hong Kong University of Science and TechnologyZeng, ZhaoyangInternational Digital Economy Academy (IDEA)Ren, Tianhe...
如ByteTrack ) 追踪检测物体。该项工作来自IDEA研究院计算机视觉与机器人研究中心（CVR，Computer Vision and Robotics）。该团队此前开源的目标检测模型DINO是首个在COCO目标检测上取得榜单第一的DETR类模型；在Github上大火的零样本检测器Grounding DINO与能够检测、分割一切的Grounded SAM，同样为该团队作品。
scenarios. We show that text prompts and visual prompts can benefit from each other within the synergy, which is essential to cover massive and complicated real-world scenarios and pave the way towards generic object detection. API code is available athttps://github.com/IDEA-Research/T-Rex....