Computer Vision News 4 Exclusive Interview of those methods. There’s one called BYOL from DeepMind – Bootstrap Your Own Latent. There are things like MoCo. There have been a number of contrastive methods to do this. I probably had the first paper on this in 1993, on a Siamese neural network. You train two identical neural nets to produce identical representations for things you know are semantically identical and then push away the outputs for dissimilar things. More recently, there’s been some progress with the SimCLR paper from Google. Then, I became somewhat negative about those contrastive methods because I don’t think they scale very well. A number of non-contrastive methods appeared about four years ago. One of them is BYOL. Another one, which came from my group at FAIR, is called Barlow Twins, and there are a number of others. Then, we came up with two other ones called VICReg and I-JEPA, or Image JEPA. Another group at FAIR worked on something called DINOv2, which works amazingly well. Those are all different ways of training a joint embedding architecture with two parallel networks and predicting the representation of one from the representation of the other. DINOv2 is applied to images, VICReg is applied to images and short videos, I-JEPA to images, and now we’re working on something called V-JEPA or Video JEPA, a version of this for video. We’ve made a lot of progress. I’mvery optimistic about wherewe’regoing. You have long been a partisan of the double affiliation model. Would you suggest young people today consider a career with hats in academia and industry, or would your advice for this generation be a little bit different? I wouldn’t advise young people at the beginning of their career to wear two hats of this type because you have to focus on one thing. In North America, if you go into academia, you have to focus on getting tenure. In Europe, it’s different, but you have to focus on building your group, your publications, your students, your brand, your research project. You can’t do this if you split your time. llll Yann’s interview with Ralph in 2018
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