Sandra
@sandra46
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My feeling is that it kinda has been for the past few years, and just doesn't seem to stop -- increasingly there is an on-going convergence of CV with General AI/ML - you saw it initially when CNNs blew every conventional computer vision methods (feature extraction, feature matching) with CNNs like AlexNet, Yolo, etc. Now with ViT vision transformers, and VLMs and the like. SAM (segment anything) is pretty amazing
That being said, edge perception stuff in the context of robotics, devices, AR/VR, and devices in general -- CV continues to be relevant. TinyML, perception models that are energy efficient and work on the edge GPU that it's meant to run on - prob a lot more work to do here, but if you look at companies like ST and TI, all they are making are MCUs that can run ML on it, so...
Also I am excited about 3D Gaussian splatting in the same way that I was excited aobut NeRFs, but 3D Gaussian splatting is a lot more efficient than NeRF - it can handle a lot more, order of magnitude more FPS. So that's cool 4 replies
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